Comments (5)
Hi, since the existing datasets are captured in simulated or laboratory environments, while UBody concentrates on real-life scenes, their distributions are quite different. Thus, I think UBody would not significantly improve the performance in these two datasets. I would do this performance in the future.
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@fatbao55 Hi, thanks for your interest in our work. We do not use UBody in the experiments of Table 3. The training sets we use in Table 3 are:
(1) Left Column: train on AGORA-train; test on AGORA-test
(2) Middle Column: train on Human3.6m, MSCOCO, MPII; test on EHF
(3) Right Column: train on Human3.6m, MSCOCO, MPII, mpi_inf_3dhp, 3DPW-train; test on 3DPW-test.
We plan to release UBody by about 15, April.
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@linjing7 Thanks for the clarification! Have you tried training with UBody dataset for experiments in Table 3? I was wondering if it could be helpful as an additional train dataset.
Looking forward to the dataset release!
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I see, thanks for clarifying!
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Is there any update on the dataset? :)
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Related Issues (20)
- ssh environment without install these libs HOT 1
- data
- environment HOT 3
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- can you not use mmpose. HOT 1
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- What is meaning "wo_decoder" HOT 4
- config HOT 1
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- J_regressor_h36m_smplx.npy file HOT 1
- Demo&CPU HOT 1
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- Errors during training! HOT 3
- 您好,请问output里cam_trans是相机的intrinsics吗?
- About ViTencoder setting HOT 1
- The image number of UBody dataset HOT 2
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