Comments (3)
I think tuning the crop as suggest in #24 (comment) to have enough zero padding as a full body may help.
But ultimately better dealing with half body capture requires re-training with this type of data (eg. using extreme crop augmentation).
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For example in SPIN, images without all major body joints are not incorporated during the training
https://github.com/nkolot/SPIN/blob/277892a91e74af004c74457cd294bd102972f9b0/datasets/preprocess/coco.py#L34-L36
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@AlexHu123 I think it is mostly engineering. A quick brute-force solution could be to post-process the data and discard the part of the mesh(set of vertices) that its joints are invisible in the image/frame. SMPL returns you all the things you want for it. During training a similar workaround is possible I think.
If you implement any of these I am happy to help merging in into the current model!
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