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OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association
[article]
2021
arXiv
pre-print
Many image-based perception tasks can be formulated as detecting, associating and tracking semantic keypoints, e.g., human body pose estimation and tracking. In this work, we present a general framework that jointly detects and forms spatio-temporal keypoint associations in a single stage, making this the first real-time pose detection and tracking algorithm. We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a
arXiv:2103.02440v2
fatcat:utj3lczi7rbqri6ntt2um2quc4