We are a research group at the Swiss Federal Institute of Technology (EPFL)'s School of Computer and Communication Sciences (IC). Our research focus is broadly on Computer Vision, Machine Learning, and Perception-for-Robotics.
4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities R. Bachmann*, O.F. Kar*, D. Mizrahi*, A. Garjani, M. Gao, D. Griffiths, J. Hu, A. Dehghan, A. Zamir NeurIPS, 2024.
Solving Vision Tasks using Simple Photoreceptors instead of Cameras A. Atanov*, J. Fu*, R. Singh*, I. Yu, A. Spielberg, A. Zamir ECCV, 2024.
ViPer: Visual Personalization of Generative Models via Individual Preference Learning S. Salehi, M. Shafiei, T. Yeo, R. Bachmann, A. Zamir ECCV, 2024.
BRAVE: Broadening the visual encoding of vision-language models O.F. Kar, A. Tonioni, P. Poklukar, A. Kulshrestha, A. Zamir, F. Tombari ECCV, 2024. [Oral]
Unraveling the Key Components of OOD Generalization via Diversification H. Benoit*, L. Jiang*, A. Atanov*, O.F. Kar, M. Rigotti, A. Zamir ICLR, 2024.
4M: Massively Multimodal Masked Modeling D. Mizrahi*, R. Bachmann*, O.F. Kar, T. Yeo, M. Gao, A. Dehghan, A. Zamir NeurIPS, 2023. [Spotlight]
Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedback T. Yeo, O.F. Kar, Z. Sodagar, A. Zamir ICCV, 2023.
Modality-invariant Visual Odometry for Embodied Navigation M. Memmel, R. Bachmann, A. Zamir CVPR, 2023.
Task Discovery: Finding the Tasks that Neural Networks Generalize on A. Atanov, A. Filatov, T. Yeo, A. Sohmshetty, A. Zamir NeurIPS, 2022.
PALMER: Perception-Action Loop with Memory Reorganization for Planning O. Beker, M. Mohammadi, A. Zamir NeurIPS, 2022.
MultiMAE: Multi-modal Multi-task Masked Autoencoders R. Bachmann*, D. Mizrahi*, A. Atanov, A. Zamir ECCV, 2022.
3D Common Corruptions and Data Augmentation O.F. Kar, T. Yeo, A. Atanov, A. Zamir CVPR, 2022. [Oral]
CLIPasso: Semantically-Aware Object Sketching Y. Vinker, E. Pajouheshgar, J. Y. Bo, R. Bachmann, A. H. Bermano, D. Cohen-Or, A. Zamir, A. Shamir Transactions on Graphics (Proceedings of SIGGRAPH), 2022. [Best Paper Award]
Robustness via Cross-Domain Ensembles T. Yeo*, O.F. Kar*, A. Zamir ICCV, 2021. [Oral]
Omnidata: A Scalable Pipeline for Making Multi-Task Mid-Level Vision Datasets from 3D Scans A. Eftekhar*, A. Sax*, R. Bachmann, J. Malik, A. Zamir ICCV, 2021.
Robust Learning Through Cross-Task Consistency A. Zamir*, A. Sax*, T. Yeo, O. Kar, N. Cheerla, R. Suri, J. Cao, J. Malik, L. Guibas CVPR, 2020. [Best Paper Award Nominee]
Which Tasks Should Be Learned Together in Multi-task Learning? T. Standley, A. Zamir, D. Chen, L. Guibas, J. Malik, S. Savarese ICML, 2020.
Side-tuning: Network Adaptation via Additive Side Networks J. Zhang, A. Sax, A. Zamir, L. Guibas, J. Malik ECCV, 2020. [Spotlight]
Robust Policies via Mid-Level Visual Representations: An Experimental Study in Manipulation and Navigation B. Chen, S. Sax, L. Pinto, F. Lewis, I. Armeni, S. Savarese, A. Zamir, J. Malik CoRL, 2020.