2k citations · 4.7k across the 40 of their papers we have counts for
9 papers · 1 filter
Learning Video Representations from Large Language Models
Yue Zhao, Ishan Misra, Philipp Krähenbühl +1
We introduce LaViLa, a new approach to learning video-language representations by leveraging Large Language Models (LLMs). We repurpose pre-trained LLMs to be conditioned on visual…
The Hidden Uniform Cluster Prior in Self-Supervised Learning
Mahmoud Assran, Randall Balestriero, Quentin Duval +6
A successful paradigm in representation learning is to perform self-supervised pretraining using tasks based on mini-batch statistics (e.g., SimCLR, VICReg, SwAV, MSN). We show tha…
MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Pose
Yang Fu, Ishan Misra, Xiaolong Wang
We propose a generalizable neural radiance fields - MonoNeRF, that can be trained on large-scale monocular videos of moving in static scenes without any ground-truth annotations of…
OmniMAE: Single Model Masked Pretraining on Images and Videos
Rohit Girdhar, Alaaeldin El-Nouby, Mannat Singh +3
Transformer-based architectures have become competitive across a variety of visual domains, most notably images and videos. While prior work studies these modalities in isolation,…
Masked Siamese Networks for Label-Efficient Learning
Mahmoud Assran, Mathilde Caron, Ishan Misra +6
We propose Masked Siamese Networks (MSN), a self-supervised learning framework for learning image representations. Our approach matches the representation of an image view containi…
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Priya Goyal, Quentin Duval, Isaac Seessel +5
Discriminative self-supervised learning allows training models on any random group of internet images, and possibly recover salient information that helps differentiate between the…