266 citations · 354 across the 10 of their papers we have counts for
8 papers · 1 filter
SAM 3: Segment Anything with Concepts
Nicolas Carion, Laura Gustafson, Yuan-Ting Hu +35
We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short…
SAM 2: Segment Anything in Images and Videos
Nikhila Ravi, Valentin Gabeur, Yuan-Ting Hu +15
We present Segment Anything Model 2 (SAM 2), a foundation model towards solving promptable visual segmentation in images and videos. We build a data engine, which improves model an…
ImageBind: One Embedding Space To Bind Them All
Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu +4
We present ImageBind, an approach to learn a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. We show that all combinations of p…
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…
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,…
Pre-train, Self-train, Distill: A simple recipe for Supersizing 3D Reconstruction
Kalyan Vasudev Alwala, Abhinav Gupta, Shubham Tulsiani
Our work learns a unified model for single-view 3D reconstruction of objects from hundreds of semantic categories. As a scalable alternative to direct 3D supervision, our work reli…
PyTorchVideo: A Deep Learning Library for Video Understanding
Haoqi Fan, Tullie Murrell, Heng Wang +13
We introduce PyTorchVideo, an open-source deep-learning library that provides a rich set of modular, efficient, and reproducible components for a variety of video understanding tas…
Revitalizing Optimization for 3D Human Pose and Shape Estimation: A Sparse Constrained Formulation
Taosha Fan, Kalyan Vasudev Alwala, Donglai Xiang +3
We propose a novel sparse constrained formulation and from it derive a real-time optimization method for 3D human pose and shape estimation. Our optimization method, SCOPE (Sparse…