304 citations · 708 across the 22 of their papers we have counts for
7 papers · 1 filter
Unsupervised Learning of Object Structure and Dynamics from Videos
Matthias Minderer, Chen Sun, Ruben Villegas +3
Extracting and predicting object structure and dynamics from videos without supervision is a major challenge in machine learning. To address this challenge, we adopt a keypoint-bas…
Learning Video Representations using Contrastive Bidirectional Transformer
Chen Sun, Fabien Baradel, Kevin Murphy +1
This paper proposes a self-supervised learning approach for video features that results in significantly improved performance on downstream tasks (such as video classification, cap…
Relational Action Forecasting
Chen Sun, Abhinav Shrivastava, Carl Vondrick +3
This paper focuses on multi-person action forecasting in videos. More precisely, given a history of H previous frames, the goal is to detect actors and to predict their future acti…
Intra-Ensemble in Neural Networks
Yuan Gao, Zixiang Cai, Lei Yu
Improving model performance is always the key problem in machine learning including deep learning. However, stand-alone neural networks always suffer from marginal effect when stac…
VideoBERT: A Joint Model for Video and Language Representation Learning
Chen Sun, Austin Myers, Carl Vondrick +2
Self-supervised learning has become increasingly important to leverage the abundance of unlabeled data available on platforms like YouTube. Whereas most existing approaches learn l…
Unsupervised Discovery of Parts, Structure, and Dynamics
Zhenjia Xu, Zhijian Liu, Chen Sun +4
Humans easily recognize object parts and their hierarchical structure by watching how they move; they can then predict how each part moves in the future. In this paper, we propose…