90 citations · 186 across the 20 of their papers we have counts for
10 papers · 1 filter
Masked Autoencoders for Egocentric Video Understanding @ Ego4D Challenge 2022
Jiachen Lei, Shuang Ma, Zhongjie Ba +3
In this report, we present our approach and empirical results of applying masked autoencoders in two egocentric video understanding tasks, namely, Object State Change Classificatio…
3DB: A Framework for Debugging Computer Vision Models
Guillaume Leclerc, Hadi Salman, Andrew Ilyas +9
We introduce 3DB: an extendable, unified framework for testing and debugging vision models using photorealistic simulation. We demonstrate, through a wide range of use cases, that…
Representation Learning for Event-based Visuomotor Policies
Sai Vemprala, Sami Mian, Ashish Kapoor
Event-based cameras are dynamic vision sensors that provide asynchronous measurements of changes in per-pixel brightness at a microsecond level. This makes them significantly faste…
Unadversarial Examples: Designing Objects for Robust Vision
Hadi Salman, Andrew Ilyas, Logan Engstrom +3
We study a class of realistic computer vision settings wherein one can influence the design of the objects being recognized. We develop a framework that leverages this capability t…
Do Adversarially Robust ImageNet Models Transfer Better?
Hadi Salman, Andrew Ilyas, Logan Engstrom +2
Transfer learning is a widely-used paradigm in deep learning, where models pre-trained on standard datasets can be efficiently adapted to downstream tasks. Typically, better pre-tr…
Modeling Affect-based Intrinsic Rewards for Exploration and Learning
Dean Zadok, Daniel McDuff, Ashish Kapoor
Positive affect has been linked to increased interest, curiosity and satisfaction in human learning. In reinforcement learning, extrinsic rewards are often sparse and difficult to…