348 citations · 1.6k across the 25 of their papers we have counts for
10 papers · 1 filter
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
Humam Alwassel, Dhruv Mahajan, Bruno Korbar +3
Visual and audio modalities are highly correlated, yet they contain different information. Their strong correlation makes it possible to predict the semantics of one from the other…
UniDual: A Unified Model for Image and Video Understanding
Yufei Wang, Du Tran, Lorenzo Torresani
Although a video is effectively a sequence of images, visual perception systems typically model images and videos separately, thus failing to exploit the correlation and the synerg…
FASTER Recurrent Networks for Efficient Video Classification
Linchao Zhu, Laura Sevilla-Lara, Du Tran +3
Typical video classification methods often divide a video into short clips, do inference on each clip independently, then aggregate the clip-level predictions to generate the video…
Learning Temporal Pose Estimation from Sparsely-Labeled Videos
Gedas Bertasius, Christoph Feichtenhofer, Du Tran +2
Modern approaches for multi-person pose estimation in video require large amounts of dense annotations. However, labeling every frame in a video is costly and labor intensive. To r…
Video Modeling with Correlation Networks
Heng Wang, Du Tran, Lorenzo Torresani +1
Motion is a salient cue to recognize actions in video. Modern action recognition models leverage motion information either explicitly by using optical flow as input or implicitly b…
Large-scale weakly-supervised pre-training for video action recognition
Deepti Ghadiyaram, Matt Feiszli, Du Tran +3
Current fully-supervised video datasets consist of only a few hundred thousand videos and fewer than a thousand domain-specific labels. This hinders the progress towards advanced v…