43 citations · 125 across the 6 of their papers we have counts for
9 papers
Learning Humanoid Locomotion over Challenging Terrain
Ilija Radosavovic, Sarthak Kamat, Trevor Darrell +1
Humanoid robots can, in principle, use their legs to go almost anywhere. Developing controllers capable of traversing diverse terrains, however, remains a considerable challenge. C…
Learning to Imitate Object Interactions from Internet Videos
Austin Patel, Andrew Wang, Ilija Radosavovic +1
We study the problem of imitating object interactions from Internet videos. This requires understanding the hand-object interactions in 4D, spatially in 3D and over time, which is…
Real-World Robot Learning with Masked Visual Pre-training
Ilija Radosavovic, Tete Xiao, Stephen James +3
In this work, we explore self-supervised visual pre-training on images from diverse, in-the-wild videos for real-world robotic tasks. Like prior work, our visual representations ar…
Learning to Learn with Generative Models of Neural Network Checkpoints
William Peebles, Ilija Radosavovic, Tim Brooks +2
We explore a data-driven approach for learning to optimize neural networks. We construct a dataset of neural network checkpoints and train a generative model on the parameters. In…
Masked Visual Pre-training for Motor Control
Tete Xiao, Ilija Radosavovic, Trevor Darrell +1
This paper shows that self-supervised visual pre-training from real-world images is effective for learning motor control tasks from pixels. We first train the visual representation…
Designing Network Design Spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick +2
In this work, we present a new network design paradigm. Our goal is to help advance the understanding of network design and discover design principles that generalize across settin…