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Bottom-up human pose estimation via disentangled keypoint regression
Z Geng, K Sun, B ** for multi-person pose estimation
Multi-person pose estimation is challenging because it localizes body keypoints for multiple
persons simultaneously. Previous methods can be divided into two streams, ie top-down …
persons simultaneously. Previous methods can be divided into two streams, ie top-down …
Zoomnas: searching for whole-body human pose estimation in the wild
This paper investigates the task of 2D whole-body human pose estimation, which aims to
localize dense landmarks on the entire human body including body, feet, face, and hands …
localize dense landmarks on the entire human body including body, feet, face, and hands …
Graph-pcnn: Two stage human pose estimation with graph pose refinement
Recently, most of the state-of-the-art human pose estimation methods are based on
heatmap regression. The final coordinates of keypoints are obtained by decoding heatmap …
heatmap regression. The final coordinates of keypoints are obtained by decoding heatmap …
When human pose estimation meets robustness: Adversarial algorithms and benchmarks
Human pose estimation is a fundamental yet challenging task in computer vision, which
aims at localizing human anatomical keypoints. However, unlike human vision that is robust …
aims at localizing human anatomical keypoints. However, unlike human vision that is robust …