UDAPose improves low-light human pose estimation by synthesizing realistic images via DHF and LCIM modules and dynamically balancing image cues with pose priors using DCA, yielding AP gains of 10.1 and 7.4 over prior methods.
Human pose estimation and its application to action recogni- tion: A survey.Journal of Visual Communication and Image Representation, 76:103055
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UDAPose: Unsupervised Domain Adaptation for Low-Light Human Pose Estimation
UDAPose improves low-light human pose estimation by synthesizing realistic images via DHF and LCIM modules and dynamically balancing image cues with pose priors using DCA, yielding AP gains of 10.1 and 7.4 over prior methods.