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SPCNet:Spatial Preserve and Content-aware Network for Human Pose Estimation
[article]
2020
arXiv
pre-print
Human pose estimation is a fundamental yet challenging task in computer vision. Although deep learning techniques have made great progress in this area, difficult scenarios (e.g., invisible keypoints, occlusions, complex multi-person scenarios, and abnormal poses) are still not well-handled. To alleviate these issues, we propose a novel Spatial Preserve and Content-aware Network(SPCNet), which includes two effective modules: Dilated Hourglass Module(DHM) and Selective Information Module(SIM).
arXiv:2004.05834v1
fatcat:3xqj4jojqnal7p7n6jill5u67u