196 citations · 458 across the 30 of their papers we have counts for
6 papers · 1 filter
Model-based Behavioral Cloning with Future Image Similarity Learning
Alan Wu, AJ Piergiovanni, Michael S. Ryoo
We present a visual imitation learning framework that enables learning of robot action policies solely based on expert samples without any robot trials. Robot exploration and on-po…
Tiny Video Networks
AJ Piergiovanni, Anelia Angelova, Michael S. Ryoo
Video understanding is a challenging problem with great impact on the abilities of autonomous agents working in the real-world. Yet, solutions so far have been computationally inte…
Evolving Losses for Unlabeled Video Representation Learning
AJ Piergiovanni, Anelia Angelova, Michael S. Ryoo
We present a new method to learn video representations from unlabeled data. Given large-scale unlabeled video data, the objective is to benefit from such data by learning a generic…
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures
Michael S. Ryoo, AJ Piergiovanni, Mingxing Tan +1
Learning to represent videos is a very challenging task both algorithmically and computationally. Standard video CNN architectures have been designed by directly extending architec…
Early Detection of Injuries in MLB Pitchers from Video
AJ Piergiovanni, Michael S. Ryoo
Injuries are a major cost in sports. Teams spend millions of dollars every year on players who are hurt and unable to play, resulting in lost games, decreased fan interest and addi…
Differentiable Grammars for Videos
AJ Piergiovanni, Anelia Angelova, Michael S. Ryoo
This paper proposes a novel algorithm which learns a formal regular grammar from real-world continuous data, such as videos. Learning latent terminals, non-terminals, and productio…