Projects per year
Abstract
Each year, thousands of people learn new visual categorization tasks -- radiologists learn to recognize tumors, birdwatchers learn to distinguish similar species, and crowd workers learn how to annotate valuable data for applications like autonomous driving. As humans learn, their brain updates the visual features it extracts and attend to, which ultimately informs their final classification decisions. In this work, we propose a novel task of tracing the evolving classification behavior of human learners as they engage in challenging visual classification tasks. We propose models that jointly extract the visual features used by learners as well as predicting the classification functions they utilize. We collect three challenging new datasets from real human learners in order to evaluate the performance of different visual knowledge tracing methods. Our results show that our recurrent models are able to predict the classification behavior of human learners on three challenging medical image and species identification tasks.
Original language | English |
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Title of host publication | Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXV |
Editors | Shai Avidan, Gabriel Brostow, Moustapha Cissé, Giovanni Maria Farinella, Tal Hassner |
Publisher | Springer |
Pages | 415-431 |
Number of pages | 17 |
ISBN (Electronic) | 978-3-031-19806-9 |
ISBN (Print) | 978-3-031-19805-2 |
DOIs | |
Publication status | Published - 20 Oct 2022 |
Event | European Conference on Computer Vision 2022 - Israel, Tel Aviv, Israel Duration: 23 Oct 2022 → 27 Oct 2022 https://eccv2022.ecva.net/ |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer Cham |
Volume | 13685 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | European Conference on Computer Vision 2022 |
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Abbreviated title | ECCV 2022 |
Country/Territory | Israel |
City | Tel Aviv |
Period | 23/10/22 → 27/10/22 |
Internet address |
Keywords / Materials (for Non-textual outputs)
- visual classification
- knowledge tracing
- human learning
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Dive into the research topics of 'Visual Knowledge Tracing'. Together they form a unique fingerprint.Projects
- 1 Finished
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Enabling advanced autonomy through human-AI collaboration
Fisher, B. (Principal Investigator), Bilen, H. (Co-investigator), Keller, F. (Co-investigator), Lascarides, A. (Co-investigator), Mac Aodha, O. (Co-investigator), Mollica, F. (Co-investigator), N, S. (Co-investigator), Ramamoorthy, R. (Co-investigator), Rovatsos, M. (Co-investigator) & Sevilla-Lara, L. (Co-investigator)
1/10/21 → 30/06/22
Project: Research