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1.Revitalizing optimization for 3d human pose and shape estimation: A sparse constrained formulation(2021)
code:No
2.Body meshes as points(2021)
regared as a two class classification task(if a grid…
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1.Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loop（2019）
collaborate regression-based (as initial pose) and iterative optimization-based approach.
code: No
2.Weakly S…
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1.HoloPose: Holistic 3D Human Reconstruction In-The-Wild(2019)
mixture-of-experts rotation prior, part-based modeling( features co-varies with joint position)
code: can not open [http://arielai.com/…
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**With Clothes**
1.Learning to reconstruct people in clothing from a single rgb camera(2019)
code:https://github.com/thmoa (no training code) (same link to 1,2,3)
2.Multi-garmentnet: Learning to…
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Hi, I am very interested in your excellent work. According to the config files of pose, there seems to be no code for 3D mesh recovery. I would like to ask how to obtain this part of the codes? Lookin…
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1.PARE: Part Attention Regressor for 3D Human Body Estimation(2021)
img-->volumetric features(before the global average pooling)-->part branch: estimates attention weights +feature branch: performs S…
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1.Shape-aware Multi-Person Pose Estimation from Multi-View Images(2021)
Part Affinity Fields (PAFs)，2d clusters candidate to 3d cluster candididate, confidence-aware votingbased algorithm.
code: htt…
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1.Delving Deep Into Hybrid Annotations for 3D Human Recovery in the Wild(2019)
In annotations used for input and supervision, dense correspondence can be more effective, or achieve same results when …
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This issue is intended to collect related papers appearing in ICCV'23/NeurIPS'23 and recent papers missed out in the survey. Please feel free to post comments if you have any suggestions!
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Will there be collection for cvpr 2023?