244 citations · 772 across the 26 of their papers we have counts for
7 papers · 1 filter
Masked Autoencoders Are Scalable Vision Learners
Kaiming He, Xinlei Chen, Saining Xie +3
This paper shows that masked autoencoders (MAE) are scalable self-supervised learners for computer vision. Our MAE approach is simple: we mask random patches of the input image and…
MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
Yanghao Li, Chao-Yuan Wu, Haoqi Fan +4
In this paper, we study Multiscale Vision Transformers (MViTv2) as a unified architecture for image and video classification, as well as object detection. We present an improved ve…
Benchmarking Detection Transfer Learning with Vision Transformers
Yanghao Li, Saining Xie, Xinlei Chen +3
Object detection is a central downstream task used to test if pre-trained network parameters confer benefits, such as improved accuracy or training speed. The complexity of object…
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…
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…
Multiscale Vision Transformers
Haoqi Fan, Bo Xiong, Karttikeya Mangalam +4
We present Multiscale Vision Transformers (MViT) for video and image recognition, by connecting the seminal idea of multiscale feature hierarchies with transformer models. Multisca…
Ego-Exo: Transferring Visual Representations from Third-person to First-person Videos
Yanghao Li, Tushar Nagarajan, Bo Xiong +1
We introduce an approach for pre-training egocentric video models using large-scale third-person video datasets. Learning from purely egocentric data is limited by low dataset scal…