162 citations · 181 across the 9 of their papers we have counts for
9 papers
Learning Higher-order Object Interactions for Keypoint-based Video Understanding
Yi Huang, Asim Kadav, Farley Lai +2
Action recognition is an important problem that requires identifying actions in video by learning complex interactions across scene actors and objects. However, modern deep-learnin…
Self-supervised Video Representation Learning with Cascade Positive Retrieval
Cheng-En Wu, Farley Lai, Yu Hen Hu +1
Self-supervised video representation learning has been shown to effectively improve downstream tasks such as video retrieval and action recognition. In this paper, we present the C…
SplitBrain: Hybrid Data and Model Parallel Deep Learning
Farley Lai, Asim Kadav, Erik Kruus
The recent success of deep learning applications has coincided with those widely available powerful computational resources for training sophisticated machine learning models with…
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only Modality
Honglu Zhou, Asim Kadav, Aviv Shamsian +6
Group Activity Recognition detects the activity collectively performed by a group of actors, which requires compositional reasoning of actors and objects. We approach the task by m…
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning
Honglu Zhou, Asim Kadav, Farley Lai +4
This paper considers the problem of spatiotemporal object-centric reasoning in videos. Central to our approach is the notion of object permanence, i.e., the ability to reason about…
15 Keypoints Is All You Need
Michael Snower, Asim Kadav, Farley Lai +1
Pose tracking is an important problem that requires identifying unique human pose-instances and matching them temporally across different frames of a video. However, existing pose…