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Human action segmentation with hierarchical supervoxel consistency
2015
2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Detailed analysis of human action, such as action classification, detection and localization has received increasing attention from the community; datasets like JHMDB have made it plausible to conduct studies analyzing the impact that such deeper information has on the greater action understanding problem. However, detailed automatic segmentation of human action has comparatively been unexplored. In this paper, we take a step in that direction and propose a hierarchical MRF model to bridge
doi:10.1109/cvpr.2015.7299000
dblp:conf/cvpr/LuXC15
fatcat:slg3lhiiabeubdk6rky52zv6ha