1.5k citations · 3.1k across the 62 of their papers we have counts for
11 papers · 1 filter
Classifying, Segmenting, and Tracking Object Instances in Video with Mask Propagation
Gedas Bertasius, Lorenzo Torresani
We introduce a method for simultaneously classifying, segmenting and tracking object instances in a video sequence. Our method, named MaskProp, adapts the popular Mask R-CNN to vid…
Listen to Look: Action Recognition by Previewing Audio
Ruohan Gao, Tae-Hyun Oh, Kristen Grauman +1
In the face of the video data deluge, today's expensive clip-level classifiers are increasingly impractical. We propose a framework for efficient action recognition in untrimmed vi…
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…
Only Time Can Tell: Discovering Temporal Data for Temporal Modeling
Laura Sevilla-Lara, Shengxin Zha, Zhicheng Yan +3
Understanding temporal information and how the visual world changes over time is a fundamental ability of intelligent systems. In video understanding, temporal information is at th…
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…
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…
Attentive Action and Context Factorization
Yang Wang, Vinh Tran, Gedas Bertasius +2
We propose a method for human action recognition, one that can localize the spatiotemporal regions that `define' the actions. This is a challenging task due to the subtlety of huma…
SCSampler: Sampling Salient Clips from Video for Efficient Action Recognition
Bruno Korbar, Du Tran, Lorenzo Torresani
While many action recognition datasets consist of collections of brief, trimmed videos each containing a relevant action, videos in the real-world (e.g., on YouTube) exhibit very d…
Video Classification with Channel-Separated Convolutional Networks
Du Tran, Heng Wang, Lorenzo Torresani +1
Group convolution has been shown to offer great computational savings in various 2D convolutional architectures for image classification. It is natural to ask: 1) if group convolut…
DistInit: Learning Video Representations Without a Single Labeled Video
Rohit Girdhar, Du Tran, Lorenzo Torresani +1
Video recognition models have progressed significantly over the past few years, evolving from shallow classifiers trained on hand-crafted features to deep spatiotemporal networks.…