48 citations · 114 across the 9 of their papers we have counts for
9 papers
Movie Gen: A Cast of Media Foundation Models
Adam Polyak, Amit Zohar, Andrew Brown +85
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…
Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioning
Rohit Girdhar, Mannat Singh, Andrew Brown +7
We present Emu Video, a text-to-video generation model that factorizes the generation into two steps: first generating an image conditioned on the text, and then generating a video…
FACET: Fairness in Computer Vision Evaluation Benchmark
Laura Gustafson, Chloe Rolland, Nikhila Ravi +5
Computer vision models have known performance disparities across attributes such as gender and skin tone. This means during tasks such as classification and detection, model perfor…
The effectiveness of MAE pre-pretraining for billion-scale pretraining
Mannat Singh, Quentin Duval, Kalyan Vasudev Alwala +9
This paper revisits the standard pretrain-then-finetune paradigm used in computer vision for visual recognition tasks. Typically, state-of-the-art foundation models are pretrained…
Learning to Substitute Ingredients in Recipes
Bahare Fatemi, Quentin Duval, Rohit Girdhar +2
Recipe personalization through ingredient substitution has the potential to help people meet their dietary needs and preferences, avoid potential allergens, and ease culinary explo…
A Simple Recipe for Competitive Low-compute Self supervised Vision Models
Quentin Duval, Ishan Misra, Nicolas Ballas
Self-supervised methods in vision have been mostly focused on large architectures as they seem to suffer from a significant performance drop for smaller architectures. In this pape…
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture
Mahmoud Assran, Quentin Duval, Ishan Misra +5
This paper demonstrates an approach for learning highly semantic image representations without relying on hand-crafted data-augmentations. We introduce the Image-based Joint-Embedd…
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…
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…