1.1k citations · 1.2k across the 4 of their papers we have counts for
5 papers
DINOv2: Learning Robust Visual Features without Supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni +23
The recent breakthroughs in natural language processing for model pretraining on large quantities of data have opened the way for similar foundation models in computer vision. Thes…
Masked Autoencoders that Listen
Po-Yao Huang, Hu Xu, Juncheng Li +5
This paper studies a simple extension of image-based Masked Autoencoders (MAE) to self-supervised representation learning from audio spectrograms. Following the Transformer encoder…
FLAVA: A Foundational Language And Vision Alignment Model
Amanpreet Singh, Ronghang Hu, Vedanuj Goswami +4
State-of-the-art vision and vision-and-language models rely on large-scale visio-linguistic pretraining for obtaining good performance on a variety of downstream tasks. Generally,…
Habitat 2.0: Training Home Assistants to Rearrange their Habitat
Andrew Szot, Alex Clegg, Eric Undersander +18
We introduce Habitat 2.0 (H2.0), a simulation platform for training virtual robots in interactive 3D environments and complex physics-enabled scenarios. We make comprehensive contr…
Influence and Passivity in Social Media
Daniel M. Romero, Wojciech Galuba, Sitaram Asur +1
The ever-increasing amount of information flowing through Social Media forces the members of these networks to compete for attention and influence by relying on other people to spr…