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Faster and better multi-person pose estimation by using a single stage with AdaptivePose

Faster and better multi-person pose estimation by using a single stage with AdaptivePose


AdaptivePose++: A Powerful Single-Stage Network for Multi-Person Pose Regression



Multi-person pose estimation generally follows top-down and bottom-up paradigms.


Both of them use an extra stage (e.g., human detection in top-down paradigm or grouping process in bottom-up paradigm) to build the relationship between the human instance and corresponding keypoints, thus leading to the high computation cost and redundant two-stage pipeline.


... propose to represent the human parts as adaptive points and introduce a fine-grained body representation method.


... deliver a compact single-stage multi-person pose regression network, termed as AdaptivePose.


During inference ... only needs a single-step decode operation to form the multi-person pose without complex post-processes and refinements.


... employ AdaptivePose for both 2D/3D multi-person pose estimation ... achieve the most competitive performance on MS COCO and CrowdPose in terms of accuracy and speed ...



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