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1 year ago | |
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associative_embedding | 1 year ago | |
cid | 1 year ago | |
dekr | 1 year ago | |
integral_regression | 1 year ago | |
rtmpose | 1 year ago | |
simcc | 1 year ago | |
topdown_heatmap | 1 year ago | |
topdown_regression | 1 year ago | |
README.md | 1 year ago |
Multi-person human pose estimation is defined as the task of detecting the poses (or keypoints) of all people from an input image.
Existing approaches can be categorized into top-down and bottom-up approaches.
Top-down methods (e.g. DeepPose) divide the task into two stages: human detection and pose estimation. They perform human detection first, followed by single-person pose estimation given human bounding boxes.
Bottom-up approaches (e.g. Associative Embedding) first detect all the keypoints and then group/associate them into person instances.
Please follow DATA Preparation to prepare data.
Please follow Demo to run demos.