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3DPW_validation_crowd_hhrnet_result.json #22

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zhLawliet opened this issue Nov 9, 2022 · 18 comments
Open

3DPW_validation_crowd_hhrnet_result.json #22

zhLawliet opened this issue Nov 9, 2022 · 18 comments

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@zhLawliet
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zhLawliet commented Nov 9, 2022

@hongsukchoi
i can‘t find the
3DPW_validation_crowd_hhrnet_result.json
J_regressor_mi_smpl.npy
MuPoTs_test_hhrnet_result.json
image

@hongsukchoi
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The 3dpw_validation_crowd_hhrnet_result.json is in the 2DPose_Detection folder.

I didn't prepare the MuPoTs evaluation code in this repo, since it has few crowd scenarios and is not a in-the-wild dataset.

@zhLawliet
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zhLawliet commented Nov 9, 2022 via email

@hongsukchoi
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I can share it. I uploaded to the joint_regressor folder.

@zhLawliet
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zhLawliet commented Nov 10, 2022 via email

@zhLawliet
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zhLawliet commented Nov 10, 2022

@hongsukchoi can you share the MuPoTs_test_hhrnet_result.json and MuPoTs_test_openpose_result.json, i want to reproduce the benchmark of MuPoTs, thanks
if i set the input_joint_name = 'gt', the pck_mean of MPJPE is 0.72376, the pck_mean of PA-MPJPE is 0.9463 ,
(pck_thresh = 150) , that's meet your expectations?

@hongsukchoi
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It takes some time to find them.

@hongsukchoi
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And if you use GT, PCK should be much higher. Does 0.72376 mean 72.376 PCK?

@zhLawliet
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zhLawliet commented Nov 16, 2022 via email

@hongsukchoi
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Here is the hhrnet result. I cannot find the openpose result :( But I remember using this repo: https://github.com/tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation

https://drive.google.com/drive/folders/1_Xrtd6k8sFv8FHh7NOg4B8pVBX-vyzS0?usp=sharing

@zhLawliet
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zhLawliet commented Nov 21, 2022 via email

@hongsukchoi
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When you run openpose, there could multiple outputs in the scene or even for one person. Filter them out with this code: https://github.com/hongsukchoi/3DCrowdNet_RELEASE/blob/main/tool/match_mupots_2dpose.py

@zhLawliet
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@hongsukchoi thanks,i have done it, i find the 3DPCK of MPJPE is just 61.2. my eval code is https://github.com/ddddwee1/MuPoTS3D-Evaluation/blob/master/util/evaluate.py
image

@hongsukchoi
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Hi,

I think there are some bugs.

  1. Use the matlab code from the original paper
  2. Check the output by comparing with the input image

@zhLawliet
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ok, i try it, if i want to get the results of paper, the chekpoint is exp_04-06_23_43 epoch10 of pretrained_3DCrowdNet?

@hongsukchoi
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Yes. I haven’t checked it before the release, but it will at least give similar results. If there’s no bug and you use detected 2d poses and gt, pck will be at least over 70 and 80 respectively.

Also, compare the joint order with the MuPoTs dataset during debugging.

@zhLawliet
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zhLawliet commented Nov 22, 2022

yes, you are right, i can get the result. by
https://github.com/mks0601/3DMPPE_POSENET_RELEASE/blob/master/data/MuPoTS/mpii_mupots_multiperson_eval.m
image

@hongsukchoi
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Great! The released pre-trained weights are for reproducing 3DPW-Crowd and 3DPW, which had the fastest convergence. If you want to reproduce the exact numbers or even higher accuracy, you can train longer. Like lr_decay: [40], end_epoch: 50

@zhLawliet
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zhLawliet commented Nov 22, 2022 via email

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