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HongwenZhang / PyMAF-X

[TPAMI 2023] PyMAF-X: Towards Well-aligned Full-body Model Regression from Monocular Images
https://www.liuyebin.com/pymaf-x
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About the training stage to reimplement the reported results on 3dpw dataset #13

Open zxk19981227 opened 1 year ago

zxk19981227 commented 1 year ago

I tried to write the training method by myself. However, i couldn't reproduce the results on 3dpw. Could you explain the training methods more detail? I tried to train the pymaf-x with the coco and itew provided in pymaf as reported in PARE, but after 15w step the results is not as well as reported in paper. Should i train the model with any other steps?

HongwenZhang commented 1 year ago

Hi, thanks for your interest in our work. Have you used the EFT labels? And how about the performance of the HMR baseline? It is also recommended to monitor the performance of 3DPW after every epoch.

zxk19981227 commented 1 year ago

Thanks for answer, i use the eft labels provided in Pymaf to train the pymafx. I want to make sure that the models' performance on 3dpw is only traind on coco and other 2d keypoints dataset?

HongwenZhang commented 1 year ago

Hi, 3D mocap datasets such as Human3.6M and MPI-INF-3DHP are also needed.

zxk19981227 commented 1 year ago

Hi, so the train have two stage. 1.train on 2d dataset 2.train on whole dataset. After these training, the model is evaluated on 3dpw?

HongwenZhang commented 1 year ago

Yes.

zxk19981227 commented 1 year ago

Hi, I hope you could provide a more detailed reproduction plan. For example, first train on the COCO and MPII data sets, and then retrain the entire data 2d+3d data set on the best checkpoints. Although I can tell you Find their detailed training methods in PARE. But in your paper, I can hardly find any specific training methods after you join the MPII data set.

HongwenZhang commented 1 year ago

Thank you for your advice.