activity
20152022
most citedDo We Need More Training Data?

204 citations · 426 across the 16 of their papers we have counts for

collaborators

25 papers

cs.CV2021

The Boombox: Visual Reconstruction from Acoustic Vibrations

Boyuan Chen, Mia Chiquier, Hod Lipson +1

Interacting with bins and containers is a fundamental task in robotics, making state estimation of the objects inside the bin critical. While robots often use cameras for state est…

cs.CV2021

Adversarial Attacks are Reversible with Natural Supervision

Chengzhi Mao, Mia Chiquier, Hao Wang +2

We find that images contain intrinsic structure that enables the reversal of many adversarial attacks. Attack vectors cause not only image classifiers to fail, but also collaterall…

cs.CV2021

Learning the Predictability of the Future

Dídac Surís, Ruoshi Liu, Carl Vondrick

We introduce a framework for learning from unlabeled video what is predictable in the future. Instead of committing up front to features to predict, our approach learns from data w…

cs.AI20206 cited

A Unifying Framework for Formal Theories of Novelty:Framework, Examples and Discussion

T. E. Boult, P. A. Grabowicz, D. S. Prijatelj +11

Managing inputs that are novel, unknown, or out-of-distribution is critical as an agent moves from the lab to the open world. Novelty-related problems include being tolerant to nov…

cs.CV20204 cited

Generative Interventions for Causal Learning

Chengzhi Mao, Augustine Cha, Amogh Gupta +3

We introduce a framework for learning robust visual representations that generalize to new viewpoints, backgrounds, and scene contexts. Discriminative models often learn naturally…

cs.CV2020

Dissecting Image Crops

Basile Van Hoorick, Carl Vondrick

The elementary operation of cropping underpins nearly every computer vision system, ranging from data augmentation and translation invariance to computational photography and repre…