42 citations · 248 across the 35 of their papers we have counts for
5 papers · 1 filter
Pose Embeddings: A Deep Architecture for Learning to Match Human Poses
Greg Mori, Caroline Pantofaru, Nisarg Kothari +4
We present a method for learning an embedding that places images of humans in similar poses nearby. This embedding can be used as a direct method of comparing images based on human…
Deep Structured Models For Group Activity Recognition
Zhiwei Deng, Mengyao Zhai, Lei Chen +4
This paper presents a deep neural-network-based hierarchical graphical model for individual and group activity recognition in surveillance scenes. Deep networks are used to recogni…
Learning Temporal Embeddings for Complex Video Analysis
Vignesh Ramanathan, Kevin Tang, Greg Mori +1
In this paper, we propose to learn temporal embeddings of video frames for complex video analysis. Large quantities of unlabeled video data can be easily obtained from the Internet…
Discovering Human Interactions in Videos with Limited Data Labeling
Mehran Khodabandeh, Arash Vahdat, Guang-Tong Zhou +4
We present a novel approach for discovering human interactions in videos. Activity understanding techniques usually require a large number of labeled examples, which are not availa…
Hierarchical Maximum-Margin Clustering
Guang-Tong Zhou, Sung Ju Hwang, Mark Schmidt +2
We present a hierarchical maximum-margin clustering method for unsupervised data analysis. Our method extends beyond flat maximum-margin clustering, and performs clustering recursi…