MHFormer
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[CVPR 2022] MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
The paper "[Occlusion-Aware Networks for 3D Human Pose Estimation in Video](https://openaccess.thecvf.com/content_ICCV_2019/papers/Cheng_Occlusion-Aware_Networks_for_3D_Human_Pose_Estimation_in_Video_ICCV_2019_paper.pdf)"[1] published in ICCV 2019 achieves 42.9 MPJPE(protocol 1) and 32.8 P-MPJPE(protocol 2) while your paper[2] achieves 43.0 MPJPE and...
When i tried to train a new model, this error occurred: File "main.py", line 117, in model_path = sorted(glob.glob(os.path.join(opt.previous_dir, '*.pth')))[1] IndexError: list index out of range I wonder why and...
I used the script provided by the P-STMO model(https://github.com/paTRICK-swk/P-STMO) to train and test the MHFormer model on the 3dhp dataset. The average value of PCK and AUC indexes obtained was...
It looks like there is no output of transition of root joint?
Line 18: "assert poses_3d is None or poses_3d[key].shape[0] == poses_3d[key].shape[0]" What's the meaning of "poses_3d[key].shape[0] == poses_3d[key].shape[0]" here? Line 22: "augment_vector = np.full(len(bounds - 1), False, dtype=bool)" What's the difference...
非常棒的工作! 我正在拼命学习你们的研究并且尝试将其应用于实际领域。 我想问的是, 1. output文件夹下的'input_2D'文件夹内是否已经是3D 人体姿势估计的结果(也就是你们论文中所描述的主要工作生成的结果)?因为我想将其用在优化虚拟人物动作中。 2. 目前使用的是略显“古老”的YOLOv3和体积很大的HRNet来工作,是否有可能将其换成新的YOLOv7和Lite-HRNet,以加快识别姿态的速度,并最终实现实时识别和多目标同时识别? 如果可行的话,能否给我讲一下修改方法?例如如何生成“ YOLOv7.weights”文件,以及能否直接在github仓库中下载Lite-HRNet来替换使用? 请原谅我作为一个cv领域的初学者可能提问过于小白,感谢您的耐心 Great Great Job! I'm trying my best to study your research and try to apply it in real world....
Hey [@Vegetebird ](https://github.com/Vegetebird)! 👋 This pull request makes it possible to run your model inside a Docker environment, which makes it easier for other people to run it. We're using...
Great Work! I am looking to evaluate mhformer model on a cross dataset. Can you guide me how can I do so? @Vegetebird
Sincerely hope that the author will open source the code of this dataset, countless people thank you for your selfless dedication. Really thank you.