activity
20152022
most citedUnadversarial Examples: Designing Objects for Robust Vision

25 citations · 96 across the 17 of their papers we have counts for

collaborators

35 papers

cs.CV20221 cited

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…

cs.LG20221 cited

Learning Modular Simulations for Homogeneous Systems

Jayesh K. Gupta, Sai Vemprala, Ashish Kapoor

Complex systems are often decomposed into modular subsystems for engineering tractability. Although various equation based white-box modeling techniques make use of such structure,…

cs.RO2022

PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training

Rogerio Bonatti, Sai Vemprala, Shuang Ma +3

Robotics has long been a field riddled with complex systems architectures whose modules and connections, whether traditional or learning-based, require significant human expertise…

cs.RO2022

Learning to Simulate Realistic LiDARs

Benoit Guillard, Sai Vemprala, Jayesh K. Gupta +4

Simulating realistic sensors is a challenging part in data generation for autonomous systems, often involving carefully handcrafted sensor design, scene properties, and physics mod…

cs.RO20221 cited

LATTE: LAnguage Trajectory TransformEr

Arthur Bucker, Luis Figueredo, Sami Haddadin +4

Natural language is one of the most intuitive ways to express human intent. However, translating instructions and commands towards robotic motion generation and deployment in the r…

cs.RO20224 cited

Reshaping Robot Trajectories Using Natural Language Commands: A Study of Multi-Modal Data Alignment Using Transformers

Arthur Bucker, Luis Figueredo, Sami Haddadin +3

Natural language is the most intuitive medium for us to interact with other people when expressing commands and instructions. However, using language is seldom an easy task when hu…