Implicit 3D Human Mesh Recovery using Consistency with Pose and Shape from Unseen-view
Author:
Affiliation:
1. Korea Advanced Institute of Science and Technology (KAIST),South Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203395.pdf?arnumber=10203395
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1. Deep learning for 3D human pose estimation and mesh recovery: A survey;Neurocomputing;2024-09
2. Updating Depth-aware Feature in the Feedback Loop for Human Mesh Recovery;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30
3. LEAPSE: Learning Environment Affordances for 3D Human Pose and Shape Estimation;IEEE Transactions on Image Processing;2024
4. Recovering 3D Human Mesh From Monocular Images: A Survey;IEEE Transactions on Pattern Analysis and Machine Intelligence;2023-12
5. Generative Approach for Probabilistic Human Mesh Recovery using Diffusion Models;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02
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