Abstract: Highlights•An iterative strategy for hand pose estimation is proposed.•A method for inverse projecting neural network features is introduced.•Pose estimation is approached from both generative and detection per- spectives.•Achieve high hand pose estimation accuracy on HO3D and DexYCB datasets.
External IDs:dblp:journals/isci/LiL25
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