Andrew David BAGDANOV

Ruolo attuale:: Professore Ordinario
SSD:: IINF-05/A - Sistemi di elaborazione delle informazioni
Afferenza organizzativa:: Dipartimento di Ingegneria dell'Informazione

Recapiti

	0552758651
	andrew.bagdanov(AT)unifi.it

Ulteriori Recapiti

	Dipartimento di Ingegneria dell\'Informazione, Stanza 287, Via Santa Marta, 3 50139 FIRENZE
	055 2758651
	andrew.bagdanov(AT)unifi.it
	http://www.micc.unifi.it/bagdanov

Avvisi

Ricevimento studenti 29 settembre 2026.

Il ricevimento studenti del 29 settembre 2026 è spostato al MICC (viale Morgagni 65, piano seminterrato).

Andrew David BAGDANOV

Orario di ricevimento (aggiornato al 11/09/2026)

Martedì alle 14:00 -- 16:00 @ Santa Marta (stanza 287)
Giovedì alle 10:00 -- 12:00 @ Santa Marta (stanza 287)
Oppure per appuntamento (o meglio su Discord)

Andrew David BAGDANOV

Biografia

Andrew D. Bagdanov ha conseguito il Bachelor of Arts in Informatica e Matematica presso l'Università del Nevada, Las Vegas, nel 1995. Ha ricevuto un Master of Science in Informatica, sempre dall'Università del Nevada, Las Vegas, nel 1996 per la sua tesi sul trattamento delle immagini digitali per applicazioni di analisi delle immagini documentarie. Ha ottenuto il dottorato di ricerca in informatica nel 2004 presso l'Università di Amsterdam con una dissertazione sul riconoscimento delle immagini documentarie basato sullo stile. Ha ricoperto una posizione post-dottorato all'Università di Firenze, dove la sua ricerca si è focalizzata sul controllo attivo delle camere, sul tracciamento e la rilevazione visiva, e sul recupero di marchi nei video sportivi. Dopo Firenze, il Dr. Bagdanov ha ricoperto una posizione di sviluppo senior presso la FAO delle Nazioni Unite a Roma, dove ha lavorato allo sviluppo di ontologie multilingue su larga scala per il recupero di informazioni agricole in oltre venti lingue. Nel 2008 è entrato nel Computer Vision Center di Barcellona, presso l'Universitat Autònoma de Barcelona, dove ha lavorato sulla visione artificiale per reti di telecamere attive e riconoscimento e rilevazione di oggetti. Nel 2011, il Dr. Bagdanov è entrato nel Media Integration and Communication Center dell'Università di Firenze, dove ha lavorato sul profiling visivo per applicazioni relative al patrimonio culturale e sulla re-identificazione delle persone.

Il Dr. Bagdanov è stato un Ramon y Cajal Fellow presso il Computer Vision Center di Barcellona ed è attualmente Professore Associato presso l'Università di Firenze ed è il coordinatore del Master in Ingegneria dell'Intelligenza Artificiale. La sua ricerca abbraccia un ampio spettro di visione artificiale, elaborazione delle immagini e apprendimento automatico. Il Prof. Bagdanov ha ricoperto posizioni professionali e accademiche in quattro paesi; è madrelingua inglese, parla fluentemente italiano e spagnolo e ha una conoscenza lavorativa del nederlandese. Ha pubblicato oltre cento articoli scientifici su riviste internazionali e atti di conferenze peer-reviewed e ha un indice h di Google Scholar di 39.

Andrew David BAGDANOV

Curriculum

DETTAGLI PERSONALI:

Prof. Andrew David BAGDANOV
Dipartimento di Ingegneria dell'Informazione
Università degli Studi di Firenze
Via S. Marta, 3 - 50139 Firenze - Italia
Email: andrew.bagdanov [AT] unifi.it

BIOGRAFIA:
Andrew D. Bagdanov ha conseguito il Bachelor of Arts in Informatica e Matematica presso l'Università del Nevada, Las Vegas, nel 1995. Ha ricevuto un Master of Science in Informatica, sempre dall'Università del Nevada, Las Vegas, nel 1996 per la sua tesi sul trattamento delle immagini digitali per applicazioni di analisi delle immagini documentarie. Ha ottenuto il dottorato di ricerca in informatica nel 2004 presso l'Università di Amsterdam con una dissertazione sul riconoscimento delle immagini documentarie basato sullo stile. Ha ricoperto una posizione post-dottorato all'Università di Firenze, dove la sua ricerca si è focalizzata sul controllo attivo delle telecamere, sul tracciamento e la rilevazione visiva, e sul recupero di marchi nei video sportivi. Dopo Firenze, il Dr. Bagdanov ha ricoperto una posizione di sviluppo senior presso la FAO delle Nazioni Unite a Roma, dove ha lavorato allo sviluppo di ontologie multilingue su larga scala per il recupero di informazioni agricole in oltre venti lingue. Nel 2008 è entrato nel Computer Vision Center di Barcellona, presso l'Universitat Autònoma de Barcelona, dove ha lavorato sulla visione artificiale per reti di telecamere attive e riconoscimento e rilevazione di oggetti. Nel 2011, il Dr. Bagdanov è entrato nel Media Integration and Communication Center dell'Università di Firenze, dove ha lavorato sul profiling visivo per applicazioni relative al patrimonio culturale e sulla re-identificazione delle persone.

Il Dr. Bagdanov è stato un Ramon y Cajal Fellow presso il Computer Vision Center di Barcellona ed è attualmente Professore Associato presso l'Università di Firenze ed è il coordinatore del Master in Ingegneria dell'Intelligenza Artificiale. La sua ricerca abbraccia un ampio spettro di visione artificiale, elaborazione delle immagini e apprendimento automatico. Il Prof. Bagdanov ha ricoperto posizioni professionali e accademiche in quattro paesi; è madrelingua inglese, parla fluentemente italiano e spagnolo e ha una conoscenza lavorativa del nederlandese. Ha pubblicato oltre cento articoli scientifici su riviste internazionali e atti di conferenze peer-reviewed e ha un indice h di Google Scholar di 39.

RIASSUNTO BIBLIOMETRICO:
Google Scholar h-Index: 39
Google Scholar i10-Index: 81

LINGUE:
Inglese (madrelingua), Italiano (fluente), Spagnolo (fluente), Olandese (avanzato).

INTERESSI DI RICERCA:
Visione artificiale, apprendimento automatico, deep learning, riconoscimento visivo degli oggetti, visione attiva, apprendimento continuo, apprendimento per rinforzo, sorveglianza video, segmentazione semantica delle immagini, re-identificazione delle persone.

ISTRUZIONE:
Dottorato di Ricerca in Informatica: Università di Amsterdam, maggio 2004.
M.Sc. in Informatica: Università del Nevada, Las Vegas, dicembre 1996.
B.A. in Informatica: Università del Nevada, Las Vegas, settembre 1995.
B.A. in Matematica: Università del Nevada, Las Vegas, settembre 1995.

ABILITAZIONI:
Abilitazione Scientifica Nazionale (ASN) 2016 (Ia fascia nel settore 01/B1, 2018).
Abilitazione Scientifica Nazionale (ASN) 2016 (Ia fascia nel settore 09/H1, 2018).

POSIZIONI ACCADEMICHE E DI RICERCA PROFESSIONALI:
Il Dr. Bagdanov ha ricoperto posizioni di ricerca in quattro paesi (Stati Uniti, Paesi Bassi, Italia e Spagna):

Professore Associato: Università di Firenze, Italia, 2015-presente.
Ramon y Cajal Fellow: Computer Vision Center, Barcellona, Spagna, 2014-2015.
Responsabile dell’Unità di Ricerca: Media Integration and Communication Center, Università di Firenze, Italia, 2011-2014.
Professore Aggiunto: Universitat Autònoma de Barcelona, Spagna, 2010-2011.
Responsabile di Progetto: Computer Vision Center, Barcellona, Spagna, 2008-2012.
Capo Sviluppo Senior: FAO delle Nazioni Unite, Roma, Italia, 2007-2008.
Ricercatore post-dottorato: Università di Firenze, Italia, 2005-2007.
Studente di dottorato/Postdoc: Università di Amsterdam, Paesi Bassi, 1999-2004.
Ingegnere di design software senior: Università del Nevada, Las Vegas, USA, 1998-1999.
Assistente alla ricerca per laureati e undergraduate: Università del Nevada, Las Vegas, USA, 1991-1997.

PARTECIPAZIONE A PROGETTI DI RICERCA COMPETITIVI FINANZIATI:
In tutte le sue posizioni accademiche, il Dr. Bagdanov ha partecipato a ricerche finanziate da organizzazioni pubbliche, private e internazionali. Di seguito sono elencati i progetti in cui ha ricoperto un ruolo importante.

Google Faculty Research Award (2017): CO-PI, finanziato per USD 38,245.00.
Interactive vision for ambient intelligent spaces (RYC-2012-11776): PI, progetto spagnolo Ramon y Cajal finanziato per EUR 308,600.
Reading in the Wild: Exploiting Text-User-Scene mutual context for reading and scene understanding (TIN2014-52072-P): CO-PI, progetto spagnolo finanziato per 109,021 EUR.
PITAGORA: Piattaforma Integrata per la Gestione delle Operazioni Aeroportuali: WP Coordinator, Progetto Regione Toscana.
MNEMOSYNE (POR-FSE 2007-2013, A.IV-OB.2): Grant holder, Progetto Regione Toscana finanziato a EUR 135,000.
HERMES IST-027110 Human-Expressive Representations of Motion and Their Evaluation in Sequences: WP Leader, Progetto STREP finanziato dall'Unione Europea a EUR 2.100.000.

TRASFERIMENTO TECNOLOGICO:
Il Dr. Bagdanov partecipa o ha partecipato ad attività di trasferimento tecnologico nel corso della sua carriera: nei Paesi Bassi (Océ - A Canon Company); in Spagna (Wide Eyes Technologies, SADAKO Technologies e CTRL4 Enviro S.L); e in Italia (Alcatel, Autostrade SPA, ALSTOM SA, Verizon Connect, Movyon SpA e Magenta SRL).

COLLEGI EDITORIALI:
Associate Editor, IEEE Transactions on Multimedia
Associate Editor, Journal on Multimedia Tools and Applications

INTERVENTI E TUTORIALS:
Istruttore alla OBA Summer School 2019 su Ottimizzazione, Big Data e Applicazioni.
Istruttore alla AI-DLDA Summer School 2020 sull'Intelligenza Artificiale.
Relatore invitato al WACV Workshop 2021 su Applicazioni di Visione e Soluzioni a Dati Bias o Scarsi.
Relatore invitato alla Seconda Conferenza Internazionale su Tecnologie Avanzate, Ingegneria Informatica e Scienza (ICATCES 2019).

ORGANIZZAZIONE DI CONFERENZE:
Area Chair, International Conference on Learning Representations (ICLR 2024).
Area Chair, International Conference on Learning Representations (ICLR 2023).
Membro, International Joint Conference on Artificial Intelligence (IJCAI) Program Committee Board (2021-2024).
Senior PC Member, International Joint Conference on Artificial Intelligence (IJCAI 2021).
Area Chair, International Conference on Learning Representations (ICLR 2021).
Area Chair, Conference on Neural Information Processing Systems (NeurIPS 2020).
Area Chair, International Conference on Pattern Recognition (ICPR 2020).
Area Chair, IEEE Winter Conference on Applications of Computer Vision (WACV 2019).
Demonstration Chair, International Conference on Computer Vision and Pattern Recognition (CVPR 2019).
Demonstration Chair, International Conference on Computer Vision (ICCV 2017).
Demonstration Chair, European Conference on Computer Vision (ECCV 2016).
Local Arrangements Chair, European Conference on Computer Vision (ECCV 2012).

SERVIZI VARI:
Revisore Esperto per il progetto europeo FP7 JUMAS.
Membro del comitato, International Association for Pattern Recognition (IAPR) Conferences and Meetings committee.
Chair Generale, Terzo Workshop Internazionale sull'Interpretazione del Layout Documentale e le sue Applicazioni (DLIA2003).
Organizzatore, Secondo Workshop Internazionale sull'Interpretazione del Layout Documentale e le sue Applicazioni (DLIA2001).

PREMI E ALTRE ONORIFICENZE:
Premio come miglior articolo per: A. Gomez-Villa, B. Twardowski, L. Yu, A. Bagdanov e J. van de Weijer, "Continually Learning Self-Supervised Representations with Projected Functional Regularization," alla 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 (Workshop CLVISION).
Google Faculty Research Award assegnato nel 2017 per la ricerca sulla modellazione congiunta di caratteristiche testuali e visive in immagini di scene naturali.
Secondo posto nella Prima THUMOS Challenge sul Riconoscimento delle Azioni con un Grande Numero di Classi con sottomissione del team MICC.
Premio come miglior articolo per: S. Karaman, A. Bagdanov, "Identity Inference: Generalizing Person Re-identification Scenarios." Primo Workshop Internazionale sulla Re-Identificazione (ECCV 2012).
Menzione d'onore, Miglior Articolo di Studente per: M. Kieu, A. D. Bagdanov, M. Bertini, A. Del Bimbo. "Domain Adaptation for Privacy-Preserving Pedestrian Detection in Thermal Imagery." ICIAP, 2019.
Vincitore della PASCAL 2010 Segmentation Challenge con sottomissione del team CVC.
Vincitore (pareggiato) della PASCAL 2010 Action Recognition Challenge con sottomissione del team CVC.
Secondo posto nella PASCAL 2009 Semantic Segmentation Challenge con entry del team CVC.
Secondo posto nella PASCAL 2009 Image Classification Challenge con entry del team CVC.

Andrew David BAGDANOV

Pubblicazioni

Legenda

Contributo su rivista |

Articolo su libro |

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Contributo in atti di convegno (proceeding) |

Brevetto |

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Tesi di Dottorato

Bagdanov; My; Bertini (In corso di stampa). Bottom-up and Layer-wise Domain Adaptation for Pedestrian Detection in Thermal Images. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING, COMMUNICATIONS AND APPLICATIONS, pp. 1-19, ISSN:1551-6857

Girolamo, Macaluso; Lorenzo, Mandelli; Bicchierai, Mirko; Berretti, Stefano; Bagdanov, Andrew D. (2026). No MoCap Needed: Post-Training Motion Diffusion Models with Reinforcement Learning using Only Textual Prompts. In: 2026 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2026, usa, 2026, Institute of Electrical and Electronics Engineers Inc., pp. 967-976. DOI

Simone Magistri, Tomaso Trinci, Albin Soutif-Cormerais, Joost van de Weijer, Andrew David Bagdanov (2026). EFC++: Elastic Feature Consolidation with Prototype Re-balancing for Cold Start Exemplar-free Incremental Learning. INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 134, pp. 0-0, ISSN:1573-1405 DOI Accesso ONLINE all'editore

Goswami, Dipam; Magistri, Simone; Wang, Kai; Twardowski, Bartłomiej; Bagdanov, Andrew; van de Weijer, Joost (2025). Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning. In: Neural Information Processing Systems (NeurIPS), Neural Information Processing Systems Foundation, Inc. (NeurIPS), pp. 72500-72534. DOI

Pjetri, Aurel; Caprasecca, Stefano; Taccari, Leonardo; Simoncini, Matteo; Monteagudo, Henrique Piñeiro; Walter, Wallace; de Andrade, Douglas Coimbra; Sambo, Francesco; Bagdanov, Andrew David (2025). ViewpointDepth: A New Dataset for Monocular Depth Estimation Under Viewpoint Shifts. In: 36th IEEE Intelligent Vehicles Symposium, IV 2025, Grand Hotel Italia, Str. Vasile Conta, nr.2, rou, 2025, Institute of Electrical and Electronics Engineers Inc., pp. 406-411, ISBN:979-8-3315-3803-3 DOI

Carlo Romeo*, Girolamo Macaluso*, Alessandro Sestini, Andrew D bagdanov (2025). SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning. REINFORCEMENT LEARNING JOURNAL, pp. 0-0, ISSN:2996-8577

Cotogni, Marco; Yang, Fei; Cusano, Claudio; Bagdanov, Andrew D.; van de Weijer, Joost (2025). Exemplar-Free Continual Learning of Vision Transformers via Gated Class-Attention and Cascaded Feature Drift Compensation. INTERNATIONAL JOURNAL OF COMPUTER VISION, pp. 1-19, ISSN:0920-5691 DOI Accesso ONLINE all'editore

Pjetri, Aurel; Abbondandolo, Davide; de Andrade, Douglas Coimbra; Caprasecca, Stefano; Sambo, Francesco; Bagdanov, Andrew David (2025). Self-supervised Road Accident Anticipation with Non-decreasing Danger. In: European Conference on Computer Vision Workshops, Springer, pp. 65-79, ISBN:9783031917660 DOI

Caselli, Lorenzo; Magistri, Simone; Bianconcini, Tommaso; Benericetti, Andrea; de Andrade, Douglas Coimbra; Bagdanov, Andrew D. (2025). Incremental and Decremental Continual Learning for Privacy-Preserving Video Recognition. In: ECCV 2024 Trust What You LearN Workshop, Springer, pp. 333-350, ISBN:9783031926471 DOI

Net, Francesc; Folia, Marc; Casals, Pep; Bagdanov, Andrew D.; Gómez, Lluis (2025). EUFCC-340K: A faceted hierarchical dataset for metadata annotation in GLAM collections. MULTIMEDIA TOOLS AND APPLICATIONS, pp. 1-24, ISSN:1573-7721 DOI

Trinci, Tomaso; Magistri, Simone; Verdecchia, Roberto; Bagdanov, Andrew D. (2025). How Green Is Continual Learning, Really? Analyzing the Energy Consumption in Continual Training of Vision Foundation Models. In: European Conference on Computer Vision, Springer, pp. 300-317, ISBN:9783031920882 DOI

Romeo, Carlo; Bagdanov, Andrew D. (2025). NTRL: Encounter Generation via Reinforcement Learning for Dynamic Difficulty Adjustment in Dungeons and Dragons. In: 2025 IEEE Conference on Games, CoG 2025, prt, 2025, IEEE Computer Society, pp. 1-8. DOI

Mistretta M.; Baldrati A.; Agnolucci L.; Bertini M.; Bagdanov A.D. (2025). CROSS THE GAP: EXPOSING THE INTRA-MODAL MISALIGNMENT IN CLIP VIA MODALITY INVERSION. In: 13th International Conference on Learning Representations, ICLR 2025, sgp, 2025, International Conference on Learning Representations, ICLR, pp. 90437-90458.

Gomez-Villa, Alex; Goswami, Dipam; Wang, Kai; Bagdanov, Andrew D.; Twardowski, Bartlomiej; van de Weijer, Joost (2025). Exemplar-Free Continual Representation Learning via Learnable Drift Compensation. In: European Conference on Computer Vision, Springer, vol. 15065 LNCS, pp. 473-490, ISBN:9783031726668 DOI

Marczak D.; Magistri S.; Cygert S.; Twardowski B.; Bagdanov A.D.; Weijer J. (2025). No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces. In: 42nd International Conference on Machine Learning, ICML 2025, can, 2025, ML Research Press, vol. 267, pp. 43177-43199.

Panariello, Aniello; Marczak, Daniel; Magistri, Simone; Porrello, Angelo; Twardowski, Bartłomiej; Bagdanov, Andrew; CALDERARA, SIMONE; van de Weijer, Joost (2025). Accurate and Efficient Low-Rank Model Merging in Core Space. In: Neural Information Processing Systems (NeurIPS), Neural Information Processing Systems Foundation, Inc. (NeurIPS), pp. 68719-68751. DOI

Girolamo Macaluso; Alessandro Sestini; Andrew D. Bagdanov (2024). Small Dataset, Big Gains: Enhancing Reinforcement Learning by Offline Pre-Training with Model-Based Augmentation. COMPUTER SCIENCES & MATHEMATICS FORUM, vol. 33, pp. 1-9, ISSN:2813-0324 DOI

Marco Mistretta; Alberto Baldrati; Marco Bertini; Andrew D. Bagdanov (2024). Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation. In: ECCV 2024, springernature, pp. 0-0.

Magistri S.; Baracchi D.; Shullani D.; Bagdanov A.D.; Piva A. (2024). Continual learning for adaptive social network identification. PATTERN RECOGNITION LETTERS, vol. 180, pp. 82-89, ISSN:0167-8655 DOI

Magistri S.; Trinci T.; Soutif-Cormerais A.; van de Weijer J.; Bagdanov A.D. (2024). ELASTIC FEATURE CONSOLIDATION FOR COLD START EXEMPLAR-FREE INCREMENTAL LEARNING. In: 12th International Conference on Learning Representations, ICLR 2024, aut, 2024, International Conference on Learning Representations, ICLR, pp. 1-23.

Mistretta, Marco; Baldrati, Alberto; Bertini, Marco; Bagdanov, Andrew D. (2024). Improving Zero-Shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation. In: European Conference on Computer Vision, Springer, pp. 459-477, ISBN:9783031729065 DOI

Liu, Xialei; Zhai, Jiang-Tian; Bagdanov, Andrew D.; Li, Ke; Cheng, Ming-Ming (2024). Task-Adaptive Saliency Guidance for Exemplar-Free Class Incremental Learning. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024, usa, 2024, IEEE Computer Society, pp. 23954-23963. DOI

Soutif-Cormerais A.; Magistri S.; van de Weijer J.; Bagdanov A.D. (2024). AN EMPIRICAL ANALYSIS OF FORGETTING IN PRE-TRAINED MODELS WITH INCREMENTAL LOW-RANK UPDATES. In: 3rd Conference on Lifelong Learning Agents, CoLLAs 2024, ita, 2024, ML Research Press, vol. 274, pp. 996-1012.

Macaluso, Girolamo; Sestini, Alessandro; Bagdanov, Andrew D. (2024). A Benchmark Environment for Offline Reinforcement Learning in Racing Games. In: IEEE Conference on Games 2024, IEEE, pp. 1-4. DOI

Camerota, Chiara; Pecorella, Tommaso; Bagdanov, Andrew D. (2024). The intrinsic convenience of federated learning in malware IoT detection. In: 20th International Conference on Network and Service Management (CNSM), Prague, 28 - 31 October 2024, IEEE, pp. 1-7. DOI

Masana, Marc; Liu, Xialei; Twardowski, Bartlomiej; Menta, Mikel; Bagdanov, Andrew D; van de Weijer, Joost (2023). Class-Incremental Learning: Survey and Performance Evaluation on Image Classification. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. PP, pp. 1-20, ISSN:0162-8828 DOI

Zini S.; Gomez-Villa A.; Buzzelli M.; Twardowski B.; Bagdanov A.D.; van de Weijer J. (2023). PLANCKIAN JITTER: COUNTERING THE COLOR-CRIPPLING EFFECTS OF COLOR JITTER ON SELF-SUPERVISED TRAINING. In: 11th International Conference on Learning Representations, ICLR 2023, rwa, 2023, International Conference on Learning Representations, ICLR, pp. 1-15.

Alessandro Sestini; Andrew Bagdanov (2023). Deep reinforcement learning for the design and validation of modern computer games. (Tutor: Andrew David Bagdanov)

Magistri S.; Baracchi D.; Shullani D.; Bagdanov A.D.; Piva A. (2023). Towards Continual Social Network Identification. In: 11th International Workshop on Biometrics and Forensics, IWBF 2023, Barcelona, Spain, April 19 th - 20 th, 2023, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, ISBN:979-8-3503-3607-8 DOI

Sestini, Alessandro; Bergdahl, Joakim; Tollmar, Konrad; Bagdanov, Andrew D.; Gisslén, Linus (2023). Towards Informed Design and Validation Assistance in Computer Games Using Imitation Learning. In: IEEE Conference on Games, IEEE, pp. 1-8. DOI

Zhai, Jiang-Tian; Liu, Xialei; Bagdanov, Andrew D.; Li, Ke; Cheng, Ming-Ming (2023). Masked Autoencoders are Efficient Class Incremental Learners. In: 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023, fra, 2023, Institute of Electrical and Electronics Engineers Inc., pp. 19047-19056. DOI

Wang K.; Wu C.; Bagdanov A.D.; Liu X.; Yang S.; Jui S.; van de Weijer J. (2022). Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification. In: 33rd British Machine Vision Conference Proceedings, BMVC 2022, gbr, 2022, British Machine Vision Association, BMVA, pp. 0-0.

Liu, Xialei; Hu, Yu-Song; Cao, Xu-Sheng; Bagdanov, Andrew D.; Li, Ke; Cheng, Ming-Ming (2022). Long-Tailed Class Incremental Learning. In: European Conference on Computer Vision (ECCV), Springer, vol. 13693, pp. 495-512, ISBN:978-3-031-19826-7 DOI

Sestini, Alessandro; Gisslen, Linus; Bergdahl, Joakim; Tollmar, Konrad; Bagdanov, Andrew D. (2022). Automated Gameplay Testing and Validation with Curiosity-Conditioned Proximal Trajectories. IEEE TRANSACTIONS ON GAMES, pp. 1-14, ISSN:2475-1510 DOI

Gomez-Villa A.; Twardowski B.; Yu L.; Bagdanov A.D.; Van De Weijer J. (2022). Continually Learning Self-Supervised Representations with Projected Functional Regularization. In: Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, vol. 2022-June, pp. 3866-3876, ISBN:978-1-6654-8739-9 DOI

Wang K.; Liu X.; Bagdanov A.; Herranz L.; Jui S.; Van De Weijer J. (2022). Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition. In: Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, vol. 2022-June, pp. 3728-3738, ISBN:978-1-6654-8739-9 DOI

Sestini A.; Kuhnle A.; Bagdanov A.D. (2021). Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents. In: 2021 IEEE Conference on Games, CoG 2021, dnk, 2021, IEEE Computer Society, vol. 2021-, pp. 01-08, ISBN:978-1-6654-3886-5 DOI

Del Chiaro R.; Bagdanov A.D.; Del Bimbo A. (2021). NoisyArt: Exploiting the NoisyWeb for Zero-shot Classification and Artwork Instance Recognition. In: Abdelhak Belhi, Abdelaziz Bouras , Abdulaziz Al-Ali, Abdul Hamid Sadka. Data Analytics for Cultural Heritage: Current Trends and Concepts, pp. 1-24 Springer International Publishing, ISBN:9783030667764. DOI

Kieu, My; Bagdanov, Andrew D.; Bertini, Marco (2021). Bottom-up and Layerwise Domain Adaptation for Pedestrian Detection in Thermal Images. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING, COMMUNICATIONS AND APPLICATIONS, vol. 17, pp. 1-19, ISSN:1551-6857 DOI

Sestini A.; Kuhnle A.; Bagdanov A.D. (2021). Demonstration-Efficient Inverse Reinforcement Learning in Procedurally Generated Environments. In: 2021 IEEE Conference on Games, CoG 2021, dnk, 2021, IEEE Computer Society, vol. 2021-, pp. 1-8, ISBN:978-1-6654-3886-5 DOI

Kieu, My; Bagdanov, Andrew D.; Bertini, Marco; del Bimbo, Alberto (2020). Task-Conditioned Domain Adaptation for Pedestrian Detection in Thermal Imagery. In: European Conference on Computer Vision, Andrea Vedaldi, Horst Bischof, Prof. Dr. Thomas Brox, Jan-Michael Frahm, vol. 12367, pp. 546-562, ISBN:978-3-030-58541-9 DOI

Riccardo Del Chiaro, Bartłomiej Twardowski, Andrew D. Bagdanov, Joost van de Weijer (2020). RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. In: Advances in Neural Information Processing Systems 33, H. Larochelle and M. Ranzato and R. Hadsell and M.F. Balcan and H. Lin, pp. 0-0.

Liu X.; Wu C.; Menta M.; Herranz L.; Raducanu B.; Bagdanov A.D.; Jui S.; Van De Weijer J. (2020). Generative feature replay for class-incremental learning. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2020, usa, 2020, IEEE Computer Society, vol. 2020-, pp. 915-924, ISBN:978-1-7281-9360-1 DOI

Pietro Bongini, Federico Becattini, Andrew David Bagdanov, Alberto del Bimbo (2020). Visual Question Answering for Cultural Heritage. In: International Conference Florence Heri-Tech, IOP Publishing, vol. 949, pp. 0-0. DOI

Kieu M.; Berlincioni L.; Galteri L.; Bertini M.; Bagdanov A.D.; Bimbo A.D. (2020). Robust pedestrian detection in thermal imagery using synthesized images. In: 25th International Conference on Pattern Recognition, ICPR 2020, ita, 2021, Institute of Electrical and Electronics Engineers Inc., pp. 8804-8811, ISBN:978-1-7281-8808-9 DOI

Del Chiaro, Riccardo; Bagdanov, Andrew D.; Del Bimbo, Alberto (2019). Webly-supervised Zero-shot Learning for Artwork Instance Recognition. PATTERN RECOGNITION LETTERS, pp. 1-11, ISSN:0167-8655 DOI

Del Bimbo, A.; Bagdanov, A; Del Chiaro, R. (2019). NoisyArt: A Dataset for Webly-supervised Artwork Recognition. In: 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Alain Tremeau; Giovanni Maria Farinella; Jose Braz, pp. 467-475, ISBN:978-989-758-354-4 DOI

Bazazian, Dena; Gã³mez, Raãºl; Nicolaou, Anguelos; Gã³mez, Lluãs; Karatzas, Dimosthenis; Bagdanov, ANDREW DAVID (2019). FAST: Facilitated and Accurate Scene Text Proposals through FCN Guided Pruning. PATTERN RECOGNITION LETTERS, pp. 1-9, ISSN:0167-8655 DOI Accesso ONLINE all'editore

Sanesi, Gianmarco; Bagdanov, Andrew D.; Bertini, Marco; Del Bimbo, Alberto (2019). DeepPhysio: Monitored Physiotherapeutic Exercise in the Comfort of your Own Home. In: ACM International Conference on Multimedia, ACM, pp. 2219-2220, ISBN:9781450368896 DOI

Bongini, Pietro; Del Chiaro, Riccardo; Bagdanov, Andrew D.; Del Bimbo, Alberto (2019). GADA: Generative Adversarial Data Augmentation for Image Quality Assessment. In: Image Analysis and Processing -- ICIAP 2019, Springer, vol. 11752, pp. 214-224, ISBN:978-3-030-30644-1 DOI

Kieu, My; Bagdanov, Andrew D.; Bertini, Marco; Del Bimbo, Alberto (2019). Domain Adaptation for Privacy-Preserving Pedestrian Detection in Thermal Imagery. In: Image Analysis and Processing – ICIAP 2019, Springer, vol. 11752, pp. 203-213, ISBN:978-3-030-30644-1 DOI

Liu, Xialei; Van De Weijer, Joost; Bagdanov, Andrew D (2019). Exploiting Unlabeled Data in CNNs by Self-supervised Learning to Rank. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, pp. 1-1, ISSN:0162-8828 DOI

Liu, Xialei; van de Weijer, Joost; Bagdanov, Andrew D. (2018). Leveraging Unlabeled Data for Crowd Counting by Learning to Rank. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, pp. 7661-7669, ISBN:978-1-5386-6420-9 DOI

Ghosh, Suman K.; Valveny, Ernest; Bagdanov, Andrew D. (2018). Visual Attention Models for Scene Text Recognition. In: 14th IAPR International Conference on Document Analysis and Recognition, ICDAR 2017, 2017, IEEE Computer Society, vol. 1, pp. 943-948, ISBN:9781538635865 DOI

Liu, XL; Masana, M; Herranz, L; Van de Weijer, J; Lopez, AM; Bagdanov, AD (2018). Rotate your Networks: Better Weight Consolidation and Less Catastrophic Forgetting. In: INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, IEEE, pp. 2262-2268. DOI

Bazazian, Dena; Karatzas, Dimosthenis; Bagdanov, Andrew D. (2018). Word spotting in scene images based on character recognition. In: 31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018, usa, 2018, IEEE Computer Society, vol. 2018-, pp. 1953-1955, ISBN:9781538661000 DOI Accesso ONLINE all'editore

Lopez fuentes, Laura; Van De Weijer, Joost; Gonzã¡lez hidalgo, Manuel; Skinnemoen, Harald; Bagdanov, ANDREW DAVID (2017). Review on computer vision techniques in emergency situations. MULTIMEDIA TOOLS AND APPLICATIONS, pp. 1-39, ISSN:1380-7501 DOI

Khan, Fahad Shahbaz; Van De Weijer, Joost; Anwer, Rao Muhammad; Bagdanov, ANDREW DAVID; Felsberg, Michael; Laaksonen, Jorma (2017). Scale coding bag of deep features for human attribute and action recognition. MACHINE VISION AND APPLICATIONS, pp. 1-17, ISSN:0932-8092 DOI

Galteri, Leonardo; Bazazian, Dena; Seidenari, Lorenzo; Bertini, Marco; Andrew D Bagdanov, ; Nicolau, Anguelos; Karatzas, Dimosthenis; Del Bimbo, Alberto (2017). Reading Text in the Wild from Compressed Images. In: International Conference on Computer Vision Workshops, Venezia, IEEE, pp. 0-0, ISBN:978-1-5386-1034-3 DOI

Liu, Xialei; Weijer, Joost van de; Bagdanov, Andrew D. (2017). RankIQA: Learning from Rankings for No-Reference Image Quality Assessment. In: International Conference on Computer Vision, Venice, Springer, pp. 1040-1049, ISBN:978-1-5386-1032-9 DOI

Masana, Marc; Weijer, Joost van de; Herranz, Luis; Bagdanov, Andrew D.; Alvarez, Jose M. (2017). Domain-Adaptive Deep Network Compression. In: International Conference on Computer Vision, Springer, pp. 4299-4307, ISBN:978-1-5386-1032-9 DOI

Lopez-Fuentes, Laura; Bagdanov, Andrew D.; Van De Weijer, Joost; Skinnemoen, Harald (2017). Bandwidth limited object recognition in high resolution imagery. In: 17th IEEE Winter Conference on Applications of Computer Vision, WACV 2017, usa, 2017, Institute of Electrical and Electronics Engineers Inc., pp. 1197-1205, ISBN:9781509048229 DOI

S. Karaman;A. Bagdanov;L. Landucci;G. D'Amico;A. Ferracani;D. Pezzatini;A. Del Bimbo (2016). Personalized multimedia content delivery on an interactive table by passive observation of museum visitors. MULTIMEDIA TOOLS AND APPLICATIONS, vol. 75, pp. 3787-3811, ISSN:1380-7501 DOI Accesso ONLINE all'editore

Cervantes, Esteve; Yu, Long Long; Bagdanov, Andrew D.; Masana, Marc; Van De Weijer, Joost (2016). Hierarchical part detection with deep neural networks. In: 23rd IEEE International Conference on Image Processing, ICIP 2016, Phoenix Convention Center, usa, 2016, IEEE Computer Society, vol. 2016-, pp. 1933-1937, ISBN:9781467399616 DOI

Nicolaou, Anguelos; Bagdanov, Andrew D.; Gomez, Lluis; Karatzas, Dimosthenis (2016). Visual Script and Language Identification. In: 12th IAPR International Workshop on Document Analysis Systems, DAS 2016, grc, 2016, Institute of Electrical and Electronics Engineers Inc., pp. 393-398, ISBN:9781509017928 DOI

Nicolaou, Anguelos; Bagdanov, Andrew D.; Liwicki, Marcus; Karatzas, Dimosthenis (2015). Sparse radial sampling LBP for writer identification. In: 13th International Conference on Document Analysis and Recognition, ICDAR 2015, Prouve Congress Center, fra, 2015, IEEE Computer Society, vol. 2015-, pp. 716-720, ISBN:9781479918058 DOI

Karatzas, Dimosthenis; Gomez-Bigorda, Lluis; Nicolaou, Anguelos; Ghosh, Suman; Bagdanov, Andrew; Iwamura, Masakazu; Matas, Jiri; Neumann, Lukas; Chandrasekhar, Vijay Ramaseshan; Lu, Shijian; Shafait, Faisal; Uchida, Seiichi; Valveny, Ernest (2015). ICDAR 2015 competition on Robust Reading. In: 13th International Conference on Document Analysis and Recognition, ICDAR 2015, Prouve Congress Center, fra, 2015, IEEE Computer Society, vol. 2015-, pp. 1156-1160, ISBN:9781479918058 DOI

G. Lisanti;I. Masi;A. Bagdanov;A. Del Bimbo (2015). Person Re-identification by Iterative Re-weighted Sparse Ranking. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 37, pp. 1629-1642, ISSN:0162-8828 DOI Accesso ONLINE all'editore

Khan, Fahad Shahbaz; Xu, Jiaolong; Van De Weijer, Joost; Bagdanov, Andrew D.; Anwer, Rao Muhammad; Lopez, Antonio M. (2015). Recognizing Actions Through Action-Specific Person Detection. IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 24, pp. 4422-4432, ISSN:1057-7149 DOI

Di Fina, Dario; Karaman, Svebor; Bagdanov, Andrew D.; Del Bimbo, Alberto (2015). MORF: Multi-Objective Random Forests for Face Characteristic Estimation. In: International Conference on Advaced Video- and Signal-based Surveillance 2015, Karlsruhe, Germany, 25-28 August, 2015, IEEE, pp. 1-6, ISBN:9781467376327 DOI

Svebor Karaman;Giuseppe Lisanti;Andrew Bagdanov;Alberto Del Bimbo (2014). From Re-identification to Identity Inference: Labeling Consistency by Local Similarity Constraints. In: Gong, Shaogang, Cristani, Marco, Yan, Shuicheng, Loy, Chen Change. Person Re-Identification, pp. 287-307 Springer London, ISBN:978-1-4471-6295-7. DOI Accesso ONLINE all'editore

F. Bartoli; G. Lisanti; S. Karaman; A. D. Bagdanov;A. Del Bimbo (2014). Unsupervised scene adaptation for faster multi-scale pedestrian detection. In: International Conference on Pattern Recognition, 2014, IEEE, pp. 3534-3539, ISBN:978-1-4799-5208-3 DOI Accesso ONLINE all'editore

Enrico Bondi;Lorenzo Seidenari;Andrew D. Bagdanov;Alberto Del Bimbo (2014). Real-time people counting from depth imagery of crowded environments. In: AVSS, IEEE, pp. 337-342, ISBN:9781479948710 DOI

Rusiñol, Marçal; Frinken, Volkmar; Karatzas, Dimosthenis; Bagdanov, Andrew D.; Lladós, Josep (2014). Multimodal page classification in administrative document image streams. INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, vol. 17, pp. 331-341, ISSN:1433-2833 DOI Accesso ONLINE all'editore

Khan, Fahad Shahbaz; Van De Weijer, Joost; Bagdanov, Andrew D.; Felsberg, Michael (2014). Scale coding bag-of-words for action recognition. In: 22nd International Conference on Pattern Recognition, ICPR 2014, swe, 2014, Institute of Electrical and Electronics Engineers Inc., pp. 1514-1519, ISBN:9781479952083 DOI Accesso ONLINE all'editore

S. Karaman;G. Lisanti;A. D. Bagdanov;A. Del Bimbo (2014). Leveraging local neighborhood topology for large scale person re-identification. PATTERN RECOGNITION, vol. 47, pp. 3767-3778, ISSN:0031-3203 DOI Accesso ONLINE all'editore

C. Baecchi*; F. Turchini*; L. Seidenari; A. D. Bagdanov; A. Del Bimbo (2014). Fisher Vectors over Random Density Forest for Object Recognition. In: ICPR, Stockholm, Sweden, ICPR, pp. ---, ISBN:978-1-4799-5209-0 DOI

Lorenzo Seidenari; Giuseppe Serra; Andrew D. Bagdanov; and Alberto Del Bimbo (2014). Local Pyramidal Descriptors for Image Recognition. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 36, pp. 1033-1040, ISSN:0162-8828 DOI

Khan, Fahad Shahbaz; Rao, Muhammad Anwer; Van De Weijer, Joost; Bagdanov, Andrew D.; Lopez, Antonio M.; Felsberg, Michael (2013). Coloring action recognition in still images. INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 105, pp. 205-221, ISSN:0920-5691 DOI

Chakraborty, Bhaskar; Bagdanov, Andrew D.; Gonzàlez, Jordi; Roca, Xavier (2013). Human action recognition using an ensemble of body-part detectors. EXPERT SYSTEMS, vol. 30, pp. 101-114, ISSN:0266-4720 DOI

Andrew Bagdanov;Alberto Del Bimbo;Dario Di Fina;Svebor Karaman;Giuseppe Lisanti;Iacopo Masi (2013). Multi-target Data Association Using Sparse Reconstruction. In: International Conference on Image Analysis and Processing, Napoli (Italia), 2013, Springer Berlin Heidelberg, vol. 8157, pp. 239-248, ISBN:9783642411830 DOI Accesso ONLINE all'editore

Iacopo Masi;Giuseppe Lisanti;Andrew D. Bagdanov;Pietro Pala;Alberto Del Bimbo (2013). Using 3D Models to Recognize 2D Faces in the Wild. In: IEEE Computer Vision and Pattern Recognition Int. Workshop on Socially Intelligent Surveillance and Monitoring (SISM), 2013-June, IEEE, pp. 775-780, ISBN:978-0-7695-4990-3 DOI

S. Karaman; A. Bagdanov; G. D'Amico; L. Landucci; A. Ferracani; D. Pezzatini; A. Del Bimbo (2013). Passive Profiling and Natural Interaction Metaphors for Personalized Multimedia Museum Experiences. In: 2nd International Workshop on Multimedia for Cultural Heritage, Naples, Italy, 2013, Springer Berlin Heidelberg, vol. 8158, pp. 247-256. DOI Accesso ONLINE all'editore

Gordo, Albert; Rusinol, Marcal; Karatzas, Dimosthenis; Bagdanov, Andrew D. (2013). Document classification and page stream segmentation for digital mailroom applications. In: 12th International Conference on Document Analysis and Recognition, ICDAR 2013, Washington, DC, usa, 2013, IEEE, pp. 621-625, ISBN:978-0-7695-4999-6 DOI

Khan, Fahad Shahbaz; Anwer, Rao Muhammad; Van De Weijer, Joost; Bagdanov, Andrew D.; Vanrell, Maria; Lopez, Antonio M. (2012). Color attributes for object detection. In: 2012 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012, Providence, RI, usa, 2012, Rama Chellapa, pp. 3306-3313, ISBN:9781467312264 DOI

Andrew Bagdanov;Alberto Del Bimbo;Giuseppe Lisanti;Iacopo Masi (2012). Multi-pose face detection for accurate face logging. In: International Conference on Pattern Recognition (ICPR), 2012, IEEE, pp. 2448-2451.

Bagdanov, Andrew D; Del Bimbo, Alberto; Masi, Iacopo (2012). Florence faces: A dataset supporting 2D/3D face recognition. In: 5th International Symposium on Communications Control and Signal Processing, ISCCSP 2012, Rome, ita, 2012, ACM, pp. 1-6, ISBN:9781467302760 DOI

Rusinol, Marcal; Karatzas, Dimosthenis; Bagdanov, Andrew D.; Llados, Josep (2012). Multipage document retrieval by textual and visual representations. In: 21st International Conference on Pattern Recognition, ICPR 2012, Tsukuba, jpn, 2012, IEEE, pp. 521-524, ISBN:9784990644109

Boix, Xavier; Gonfaus, Josep M.; Van De Weijer, Joost; Bagdanov, Andrew D.; Serrat, Joan; Gonzàlez, Jordi (2012). Harmony potentials : Fusing global and local scale for semantic image segmentation. INTERNATIONAL JOURNAL OF COMPUTER VISION, vol. 96, pp. 83-102, ISSN:0920-5691 DOI

Smeulders, Arnold W. M.*; Bagdanov, Andrew D. (2012). Color Feature Detection. In: Theo Gevers, Arjan Gijsenij, Joost van de Weijer, Jan-Mark Geusebroek, and Arnold W. M. Smeulders. Color in Computer Vision: Fundamentals and Applications, pp. 188-220 John Wiley and Sons, ISBN:9780470890844. DOI Accesso ONLINE all'editore

Bagdanov, Andrew D; Del Bimbo, Alberto; Landucci, Lea; Pernici, Federico (2012). MNEMOSYNE: Enhancing the museum experience through interactive media and visual profiling. In: 1st International Workshop on Multimedia for Cultural Heritage, MM4CH 2011, Modena, ita, 2011, Costantino Grana, Rita Cucchiara, vol. 247, pp. 38-50, ISBN:9783642279775 DOI

Karaman, Svebor; Bagdanov, Andrew D. (2012). Identity inference: Generalizing person re-identification scenarios. In: 12th European Conference on Computer Vision, ECCV 2012, Florence, ita, 2012, LNCS, vol. 7583, pp. 443-452, ISBN:9783642338625 DOI Accesso ONLINE all'editore

Cucchiara, Rita; Grana, Costantino; Borghesani, Daniele; Agosti, Maristella; Bagdanov, Andrew D. (2012). Multimedia for cultural heritage: Key issues. In: 1st International Workshop on Multimedia for Cultural Heritage, MM4CH 2011, Modena, ita, 2011, Springer, vol. 247, pp. 206-216, ISBN:9783642279775 DOI

Andrew D. Bagdanov;Alberto Del Bimbo;Fabrizio Dini;Giuseppe Lisanti;Iacopo Masi (2012). Posterity Logging of Face Imagery for Video Surveillance. IEEE MULTIMEDIA, vol. 19, pp. 48-59, ISSN:1070-986X DOI

A. D. Bagdanov; A. Del Bimbo; L. Seidenari; L. Usai (2012). Real-time hand status recognition from RGB-D imagery. In: International Conference on Pattern Recognition, Novembre 2012, IEEE, pp. 2456-2459. Accesso ONLINE all'editore

A. D. Bagdanov;M. Bertini;A. Del Bimbo;L. Seidenari (2011). Adaptive Video Compression for Video Surveillance Applications. In: International Symposium on Multimedia, 2011-December, IEEE, pp. 190-197. DOI Accesso ONLINE all'editore

A. D. Bagdanov;A. Del Bimbo;I. Masi (2011). The Florence 2D/3D Hybrid Face Dataset. In: ACM Multimedia 2011, Scottsdale, Phoenix Arizona, ACM, pp. 79-80.

Amato, Ariel; Mozerov, Mikhail G.; Bagdanov, Andrew D.; Gonzalez, Jordi (2011). Accurate moving cast shadow suppression based on local color constancy detection. IEEE TRANSACTIONS ON IMAGE PROCESSING, vol. 20, pp. 2954-2966, ISSN:1057-7149 DOI

Khan, Fahad Shahbaz; Van De Weijer, Joost; Bagdanov, Andrew D.; Vanrell, Maria (2011). Portmanteau vocabularies for multi-cue image representation. In: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011, Granada, esp, 2011, Terrence Sejnowski, pp. 1-9, ISBN:9781618395993

Pedersoli, Marco; Gonzlez, Jordi; Bagdanov, Andrew D.; Roca, Xavier (2011). Efficient discriminative multiresolution cascade for real-time human detection applications. PATTERN RECOGNITION LETTERS, vol. 32, pp. 1581-1587, ISSN:0167-8655 DOI

Gonfaus, Josep M.; Boix, Xavier; Van De Weijer, Joost; Bagdanov, Andrew D.; Serrat, Joan; Gonzàlez, Jordi (2010). Harmony potentials for joint classification and segmentation. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, usa, 2010, IEEE, pp. 3280-3287, ISBN:9781424469840 DOI

Gong, Wenjuan*; Bagdanov, Andrew D.; Roca, F. Xavier; Gonzàlez, Jordi (2010). Automatic key pose selection for 3D human action recognition. In: 6th International Conference on Articulated Motion and Deformable Objects, AMDO 2010, Port d'Andratx, Mallorca, esp, 2010, Springer, vol. 6169, pp. 290-299, ISBN:3642140602 DOI

Al Haj, Murad*; Bagdanov, Andrew D.; Gonzàlez, Jordi; Roca, F. Xavier (2010). Reactive object tracking with a single PTZ camera. In: 2010 20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, tur, 2010, IEEE, pp. 1690-1693, ISBN:9780769541099 DOI

Pedersoli, Marco; Gonzàlez, Jordi; Bagdanov, Andrew D.; Villanueva, Juan J. (2010). Recursive coarse-to-fine localization for fast object detection. In: 11th European Conference on Computer Vision, ECCV 2010, Heraklion, Crete, grc, 2010, Springer, vol. 6316, pp. 280-293, ISBN:3642155669 DOI

Haj, Murad Al; Bagdanov, Andrew D.; Gonzàlez, Jordi; Roca, Xavier F. (2009). Robust and efficient multipose face detection using skin color segmentation. In: 4th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2009, Povoa de Varzim, prt, 2009, Springer, vol. 5524, pp. 152-159, ISBN:3642021719 DOI

Chakraborty, Bhaskar; Bagdanov, Andrew D.; Gonzàlez, Jordi (2009). Towards real-time human action recognition. In: 4th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2009, Povoa de Varzim, prt, 2009, Springer, vol. 5524, pp. 425-432, ISBN:3642021719 DOI

A. D. Bagdanov; F. Dini; A. Del Bimbo; W. Nunziati (2007). Adaptive uncertainty estimation for particle filter-based trackers. In: ICIAP, IEEE, pp. 331-336.

A. D. Bagdanov; F. Dini; A. Del Bimbo; W. Nunziati (2007). Improving the robustness of particle filter-based visual trackers using online parameter adaptation. In: AVSS, London, gbr, 2007, IEEE, pp. 218-223, ISBN:9781424416967 DOI

Andrew D. Bagdanov; Lamberto Ballan; Marco Bertini; Alberto Del Bimbo (2007). Trademark matching and retrieval in sports video databases. In: 9th ACM SIGMM International Workshop on Multimedia Information Retrieval (MIR), Augsburg, Germany, 2007, ACM, pp. 79-86. DOI

Andrew D. Bagdanov; Marco Bertini; Alberto Del Bimbo; Giuseppe Serra; Carlo Torniai (2007). Semantic annotation and retrieval of video events using multimedia ontologies. In: International Conference on Semantic Computing (ICSC), 2007-#sep#, pp. 713-720.

Bagdanov, Andrew D; Del Bimbo, Alberto; Nunziati, Walter; Pernici, Federico (2006). Learning foveal sensing strategies in unconstrained surveillance environments. In: IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006, Sydney, NSW, aus, 2006, ieee, pp. 40-40, ISBN:0769526888 DOI

Bagdanov, Andrew D; Del Bimbo, Alberto; Nunziati, Walter; Pernici, Federico (2006). A reinforcement learning approach to active camera foveation. In: 4th ACM International Workshop on Video Surveillance and Sensor Networks, VSSN'06, co-located with the 2006 ACM International Multimedia Conference, Santa Barbara, CA, usa, 2007, ACM, pp. 179-186, ISBN:1595934960 DOI

Van De Weijer, Joost; Gevers, Theo; Bagdanov, Andrew D. (2006). Boosting color saliency in image feature detection. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, vol. 28, pp. 150-156, ISSN:0162-8828 DOI

Bagdanov, Andrew D; Del Bimbo, Alberto; Nunziati, Walter (2006). Improving evidential quality of surveillance imagery through active face tracking. In: 18th International Conference on Pattern Recognition, ICPR 2006, Hong Kong, chn, 2006, N/A, vol. 3, pp. 1200-1203, ISBN:0769525210 DOI

Bagdanov, Andrew D.; Del Bimbo, Alberto; Pernici, Federico (2005). Acquisition of high-resolution images through online saccade sequence planning. In: 3rd ACM International Workshop on Video Surveillance and Sensor Networks, VSSN 2005, sgp, 2005, Association for Computing Machinery, Inc, pp. 121-129, ISBN:1595932429 DOI

Seinstra, F. J.; Koelma, D.; Bagdanov, A. D. (2004). Towards User Transparent Data and Task Parallel Image and Video Processing: An Overview of the Parallel-Horus Project. In: Euro-Par 2004 Parallel Processing, Springer, vol. 3149, pp. 752-759, ISBN:978-3-540-22924-7 DOI

Seinstra, Frank J; Koelma, Dennis; Bagdanov, Andrew D. (2004). Finite state machine-based optimization of data parallel regular domain problems applied in low-level image processing. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, vol. 15, pp. 865-877, ISSN:1045-9219 DOI

Bagdanov, Andrew D; Worring, Marcel (2003). First order Gaussian graphs for efficient structure classification. PATTERN RECOGNITION, vol. 36, pp. 1311-1324, ISSN:0031-3203 DOI

Bagdanov, Andrew D.*; Worring, Marcel (2003). Multiscale document description using rectangular granulometries. INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, vol. 6, pp. 181-191, ISSN:1433-2833 DOI

Klein, Bertin; Agne, Stefan; Bagdanov, Andrew D. (2003). Understanding document analysis and understanding (through modeling). In: 7th International Conference on Document Analysis and Recognition, ICDAR 2003, gbr, 2003, IEEE Computer Society, vol. 2003-, pp. 1218-1222, ISBN:0769519601 DOI

Bagdanov, A.D.; Worring, M. (2002). Granulometric analysis of document images. In: International Conference on Pattern Recognition, IEEE, vol. 1, pp. 468-471, ISBN:0-7695-1695-X DOI

Worring, Marcel; Bagdanov, Andrew; Gemert, Jan V.; Geusebroek, Jan-Mark; Minh, Hoang; Schreiber, Guus; Snoek, Cees; Vendrig, Jeroen; Wielemaker, Jan; Smeulders, Arnold (2002). Interactive indexing and retrieval of multimedia content. In: 29th Conference on Current Trends in Theory and Practice of Informatics, SOFSEM 2002, Milovy, cze, 2002, Springer Verlag, vol. 2540, pp. 135-148, ISBN:354000145X DOI Accesso ONLINE all'editore

Bagdanov, Andrew D.; Worring, Marcel (2001). Fine-grained document genre classification using first order random graphs. In: 6th International Conference on Document Analysis and Recognition, ICDAR 2001, usa, 2001, IEEE Computer Society, vol. 2001-, pp. 79-83, ISBN:0769512631 DOI

Kanai, Junichi; Bagdanov, Andrew D. (1998). Projection profile based skew estimation algorithm for JBIG compressed images. INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, vol. 1, pp. 43-51, ISSN:1433-2833 DOI

Bagdanov, Andrew D.; Kanai, Junichi (1996). Evaluation of document image skew estimation techniques. In: PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING, SPIE, vol. 2660, pp. 343-353. DOI

Andrew David BAGDANOV

Biography

Andrew D. Bagdanov received the Bachelor of Arts in Computer Science and Mathematics from the University of Nevada, Las Vegas, in 1995. He received a Masters of Science in Computer Science, also from the University of Nevada, Las Vegas, in 1996 for his thesis on digital image processing for document image analysis applications. He obtained his PhD in computer science in 2004 from the University of Amsterdam for his PhD dissertation on style-based document image understanding. He held a postdoctoral position at the University of Florence, where his research focused on active camera control, visual tracking and detection, and retrieval of trademarks in sports videos. After Florence, Dr. Bagdanov held a senior development position at the FAO of the United Nations in Rome where he worked on developing large-scale, multilingual ontologies for cross-language retrieval of agricultural information in over twenty languages. In 2008 he joined the Computer Vision Center, Barcelona, at the Universitat Autonoma de Barcelona where he worked on computer vision for active camera networks and object recognition and detection. In 2011, Dr. Bagdanov joined the Media Integration and Communication Center at the University of Florence where he worked on visual profiling for cultural heritage applications and person re-identification.

Dr. Bagdanov was a Ramon y Cajal Fellow at the Computer Vision Center, Barcelona, and is currently Associate Professor at the University of Florence and is the coordinator of the Masters Program in Artificial Intelligence Engineering. His research spans a broad spectrum of computer vision, image processing and machine learning. Prof. Bagdanov has held professional and academic positions in four countries; he is a native English speaker, speaks Italian and Spanish fluently, and has a working knowledge of Dutch. He has published over one hundred scientific articles in peer-reviewed, international journals and conference proceedings and has a Google Scholar h-index of 37.

Andrew David BAGDANOV

Curriculum

PERSONAL DETAILS:
Prof. Andrew David BAGDANOV
Dipartimento di Ingegneria dell'Informazione
Università degli Studi di Firenze
Via S. Marta, 3 - 50139 Firenze - Italy
Email: andrew.bagdanov [AT] unifi.it

BIOGRAPHY:
Andrew D. Bagdanov received the Bachelor of Arts in Computer Science and Mathematics from the University of Nevada, Las Vegas, in 1995. He received a Masters of Science in Computer Science, also from the University of Nevada, Las Vegas, in 1996 for his thesis on digital image processing for document image analysis applications. He obtained his PhD in computer science in 2004 from the University of Amsterdam for his PhD dissertation on style-based document image understanding. He held a postdoctoral position at the University of Florence, where his research focused on active camera control, visual tracking and detection, and retrieval of trademarks in sports videos. After Florence, Dr. Bagdanov held a senior development position at the FAO of the United Nations in Rome where he worked on developing large-scale, multilingual ontologies for cross-language retrieval of agricultural information in over twenty languages. In 2008 he joined the Computer Vision Center, Barcelona, at the Universitat Autonoma de Barcelona where he worked on computer vision for active camera networks and object recognition and detection. In 2011, Dr. Bagdanov joined the Media Integration and Communication Center at the University of Florence where he worked on visual profiling for cultural heritage applications and person re-identification.

Dr. Bagdanov was a Ramon y Cajal Fellow at the Computer Vision Center, Barcelona, and is currently Associate Professor at the University of Florence and is the coordinator of the Masters Program in Artificial Intelligence Engineering. His research spans a broad spectrum of computer vision, image processing and machine learning. Prof. Bagdanov has held professional and academic positions in four countries; he is a native English speaker, speaks Italian and Spanish fluently, and has a working knowledge of Dutch. He has published over one hundred scientific articles in peer-reviewed, international journals and conference proceedings and has a Google Scholar h-index of 37.

BIBLIOMETRIC SUMMARY:
Google Scholar h-Index: 39
Google Scholar i10-Index: 81

LANGUAGES:
English (native), Italian (fluent), Spanish (fluent), Dutch (advanced).

RESEARCH INTERESTS:
Computer vision, machine learning, deep learning, computer vision, visual object recognition, active vision, continual learning, reinforcement learning, video surveillance, semantic image segmentation, person re-identification.

EDUCATION:
Ph.D. in Computer Science: University of Amsterdam, May, 2004.
M.Sc. in Computer Science: University of Nevada, Las Vegas. December, 1996.
B.A. in Computer Science: University of Nevada, Las Vegas, September, 1995.
B.A. in Mathematics: University of Nevada, Las Vegas, September, 1995.

ACCREDITATION:
Abilitazione Scientifica Nazionale (ASN) 2016 (Ia fascia nel settore 01/B1, 2018).
Abilitazione Scientifica Nazionale (ASN) 2016 (Ia fascia nel settore 09/H1, 2018).

ACADEMIC AND PROFESSIONAL RESEARCH POSITIONS HELD:
Dr. Bagdanov has held research positions in four countries (The United States, The Netherlands, Italy and Spain):

Associate Professor: University of Florence, Italy, 2015-present.
Ramon y Cajal Fellow: Computer Vision Center, Barcelona, Spain, 2014-2015.
Head of Research Unit: Media Integration and Communication Center, University of Florence, Italy, 2011-2014.
Adjunct Professor: Universitat Autónoma de Barcelona, Spain, 2010-2011.
Project Leader: Computer Vision Center, Barcelona, Spain, 2008-2012.
Senior Development Chief: FAO of the United Nations, Rome, Italy, 2007-2008.
Postdoctoral researcher: University of Florence, Italy, 2005-2007.
Ph.D. Student/Postdoc: University of Amsterdam, The Netherlands, 1999-2004.
Senior Software Design Engineer:, University of Nevada, Las Vegas, USA, 1998-1999.
Undergraduate and Graduate Research Assistant: University of Nevada, Las Vegas, USA, 1991-1997

PHD STUDENT SUPERVISION:

Simone Magistri, University of Florence, Italy. Thesis TBD (March 2024, anticipated).
Pietro Bongini, University of Florence, Italy. Thesis: Vision and Language Tasks: Applications to Real Scenarios and Image Quality
Assessment (March, 2023).
Alessandro Sestini, University of Florence, Italy. Thesis: Deep Reinforcement Learning for the Design and Validation of Modern Computer Games (June, 2023).
Riccardo Del Chiaro, University of Florence, Italy. Thesis: Anthropomorphous Visual Recognition (June, 2021).
My Kieu, University of Florence, Italy. Thesis: Deep Domain Adaptation for Pedestrian Detection in Thermal Imagery (June 2021).
Laura Lopez-Fuentes, Universitat Autónoma de Barcelona, Spain. Thesis: Semantic Computer Vision Tools for Mission-Critical Visual Communications (April, 2021).
Marc Masana, Universitat Autónoma de Barcelona, Spain. Thesis: Lifelong Learning of Neural Networks (November, 2020).
Xia-lei Liu, Universitat Autónoma de Barcelona, Spain. Thesis: Visual recognition in the wild (December, 2019).
Dena Bazazian, Universitat Autónoma de Barcelona, Spain. Thesis: Fully Convolutional Networks for Text Understanding in Scene Images (November, 2018).
Dario Di Fina, University of Florence, Italy. Thesis: Multi-Target Tracking and Facial Attribute Estimation in Smart Environments (December 2015).
Iacopo Masi, University of Florence, Italy. Thesis: From Motion to Faces: 3D-assisted automatic analysis of people (March 2014).
Murad al Haj, Universitat Autónoma de Barcelona, Spain. Thesis: From images to scenes: active scene understanding (February 2013).
Bhaskar Chakraboorthy, Universitat Autónoma de Barcelona, Spain. Thesis: Model-free approaches to human action recognition (December 2012).

PARTICIPATION IN FUNDED COMPETITIVE RESEARCH PROJECTS:
In all of his academic positions, Dr. Bagdanov has participated in research funded by public, private, and international organizations. Here are listed the projects in which he played an important role.

Google Faculty Research Award (2017): CO-PI, funded for USD 38,245.00.
Interactive vision for ambient intelligent spaces (RYC-2012-11776): PI, Spanish Ramon y Cajal project funded for EUR 308,600.
Reading in the Wild: Exploiting Text-User-Scene mutual context for reading and scene understanding (TIN2014-52072-P): CO-PI, Spanish project funded for 109,021 EUR.
PITAGORA: Piattaforma Integrata per la Gestione delle Operazioni Aeroportuali: WP Coordinator, Region of Tuscany Project.
MNEMOSYNE (POR-FSE 2007-2013, A.IV-OB.2): Grant holder, Region of Tuscany Project funded at EUR 135,000.
HERMES IST-027110 Human-Expressive Representations of Motion and Their Evaluation in Sequences: WP Leader, STREP Project funded by European Union ad EUR 2.100.000.

TECHNOLOGY TRANSFER:
Dr. Bagdanov participates or has participated in technology transfer activities throughout his career: in The Netherlands (Océ - A Canon Company); in Spain (Wide Eyes Technologies, SADAKO Technologies, and CTRL4 Enviro S.L); and in Italy (Alcatel, Autostrade SPA, ALSTOM SA, Verizon Connect, Movyon SpA, and Magenta SRL).

EDITORIAL BOARDS:

Associate Editor, IEEE Transactions on Multimedia
Associate Editor, Journal on Multimedia Tools and Applications

INVITED TALKS AND TUTORIALS

Instructor at the 2019 OBA Summer School on Optimization, Big Data and Applications.
Instructor at the 2020 AI-DLDA Summer School on Artificial Intelligence.
Invited speaker at the 2021 WACV Workshop on Vision Applications & Solution to Biased or Scarce Data.
Invited speaker at the 2nd International Conference on Advanced Technologies, Computer Engineering and Science (ICATCES 2019).

CONFERENCE ORGANIZATION:

Area Chair, International Conference on Learning Representations (ICLR 2024).
Area Chair, International Conference on Learning Representations (ICLR 2023).
Member, International Joint Conference on Artificial Intelligence (IJCAI) Program Committee Board (2021--2024).
Senior PC Member}, International Joint Conference on Artificial Intelligence (IJCAI 2021).
Area Chair, International Conference on Learning Representations (ICLR 2021).
Area Chair, Conference on Neural Information Processing Systems (NeurIPS 2020).
Area Chair, International Conference on Pattern Recognition (ICPR 2020).
Area Chair, IEEE Winter Conference on Applications of Computer Vision (WACV 2019).
Demonstration Chair, International Conference on Computer Vision and Pattern Recognition (CVPR 2019).
Demonstration Chair, International Conference on Computer Vision (ICCV 2017).
Demonstration Chair, European Conference on Computer Vision (ECCV 2016).
Local Arrangements Chair, European Conference on Computer Vision (ECCV 2012).

MISCELLANEOUS SERVICE:

Expert Reviewer for FP7 European project JUMAS.
Committee member, International Association for Pattern Recognition (IAPR) Conferences and Meetings committee.
General Chair, Third International Workshop on Document Layout Interpretation and its Applications (DLIA2003).
Organizer, Second International Workshop on Document Layout Interpretation and its Applications (DLIA2001).

AWARDS AND OTHER HONORS:

Best paper award for: A. Gomez-Villa, B. Twardowski, L. Yu, A. Bagdanov and J. van de Weijer, "Continually Learning Self-Supervised Representations with Projected Functional Regularization," in 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2022 (CLVISION Workshop),
Google Faculty Research Award awarded in 2017 for research on joint text/visual feature modeling in natural scene images.
Second place in First THUMOS Challenge on Action Recognition with a Large Number of Classes with MICC team submission.
Best paper award for: S. Karaman, A. Bagdanov, "Identity Inference: Generalizing Person Re-identification Scenarios." First International Workshop on Re-Identification (ECCV 2012).
Honorable mention, Best Student Paper Award for: M. Kieu, A. D. Bagdanov, M. Bertini, A. Del Bimbo. "Domain Adaptation for Privacy-Preserving Pedestrian Detection in Thermal Imagery." ICIAP, 2019.
Winner of PASCAL 2010 Segmentation Challenge with CVC team submission.
Winner (tied) of PASCAL 2010 Action Recognition Challenge with CVC team submission.
Second place in PASCAL 2009 Semantic Segmentation Challenge with CVC team entry.
Second place in PASCAL 2009 Image Classification Challenge with CVC team entry.