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OmniPose: A Multi-Scale Framework for Multi-Person Pose Estimation
[article]
2021
arXiv
pre-print
We propose OmniPose, a single-pass, end-to-end trainable framework, that achieves state-of-the-art results for multi-person pose estimation. Using a novel waterfall module, the OmniPose architecture leverages multi-scale feature representations that increase the effectiveness of backbone feature extractors, without the need for post-processing. OmniPose incorporates contextual information across scales and joint localization with Gaussian heatmap modulation at the multi-scale feature extractor
arXiv:2103.10180v1
fatcat:lxxogynllbaf5ia4znpypchiku