103 citations · 253 across the 13 of their papers we have counts for
10 papers · 1 filter
An Empirical Study of Autoregressive Pre-training from Videos
Jathushan Rajasegaran, Ilija Radosavovic, Rahul Ravishankar +3
We empirically study autoregressive pre-training from videos. To perform our study, we construct a series of autoregressive video models, called Toto. We treat videos as sequences…
Reconstructing Hands in 3D with Transformers
Georgios Pavlakos, Dandan Shan, Ilija Radosavovic +3
We present an approach that can reconstruct hands in 3D from monocular input. Our approach for Hand Mesh Recovery, HaMeR, follows a fully transformer-based architecture and can ana…
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…
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…
Ego4D: Around the World in 3,000 Hours of Egocentric Video
Kristen Grauman, Andrew Westbury, Eugene Byrne +82
We introduce Ego4D, a massive-scale egocentric video dataset and benchmark suite. It offers 3,670 hours of daily-life activity video spanning hundreds of scenarios (household, outd…
Reconstructing Hand-Object Interactions in the Wild
Zhe Cao, Ilija Radosavovic, Angjoo Kanazawa +1
In this work we explore reconstructing hand-object interactions in the wild. The core challenge of this problem is the lack of appropriate 3D labeled data. To overcome this issue,…
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…
On Network Design Spaces for Visual Recognition
Ilija Radosavovic, Justin Johnson, Saining Xie +2
Over the past several years progress in designing better neural network architectures for visual recognition has been substantial. To help sustain this rate of progress, in this wo…
Attentive Single-Tasking of Multiple Tasks
Kevis-Kokitsi Maninis, Ilija Radosavovic, Iasonas Kokkinos
In this work we address task interference in universal networks by considering that a network is trained on multiple tasks, but performs one task at a time, an approach we refer to…
Data Distillation: Towards Omni-Supervised Learning
Ilija Radosavovic, Piotr Dollár, Ross Girshick +2
We investigate omni-supervised learning, a special regime of semi-supervised learning in which the learner exploits all available labeled data plus internet-scale sources of unlabe…