75 citations · 303 across the 30 of their papers we have counts for
6 papers · 1 filter
Overcoming Mode Collapse with Adaptive Multi Adversarial Training
Karttikeya Mangalam, Rohin Garg
Generative Adversarial Networks (GANs) are a class of generative models used for various applications, but they have been known to suffer from the mode collapse problem, in which s…
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…
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…
Object-Region Video Transformers
Roei Herzig, Elad Ben-Avraham, Karttikeya Mangalam +5
Recently, video transformers have shown great success in video understanding, exceeding CNN performance; yet existing video transformer models do not explicitly model objects, alth…
LOKI: Long Term and Key Intentions for Trajectory Prediction
Harshayu Girase, Haiming Gang, Srikanth Malla +4
Recent advances in trajectory prediction have shown that explicit reasoning about agents' intent is important to accurately forecast their motion. However, the current research act…
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…