edz-o / 3dnbf Goto Github PK
View Code? Open in Web Editor NEWOfficial code base for the ICCV 2023 paper "3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation"
License: Apache License 2.0
Official code base for the ICCV 2023 paper "3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation"
License: Apache License 2.0
I'd like to use your pre-trained model to reconstruct videos and images. Could you please guide me on how to test this? I'm very grateful for your assistance.
Thanks for your excellent work.
When I run the demo part, the result is like this:
When I uncommented these two lines of code, and run this command CUDA_VISIBLE_DEVICES=0 python tools/visualize_predictions.py --config configs/3dnbf/resnet50_pare_w_coke_pw3d_demo.py --output_file output/result_keypoints.json --outdir output/visualization
again, the result became like this:
3DNBF/tools/visualize_predictions.py
Lines 149 to 150 in 3f9e868
I want to know why the human body model is not displayed on my demo results.
Thanks in advance.
Hi @edz-o et al.,
Thx for ur exellent work. May I ask it seems the occ
model is never activated for all given configs, no? If I understood correctly, a Bernoulli is used to model occ? Any clarification would help! Thx in advance & best,
As stated in the paper:
but note that we are using a robust likelihood during inference. (Sec. 3.2)
Hi @edz-o @Angtian @AdamKortylewski et al.,
It would be good if u could clarify where 2-stage is implemented in the current codebase. I have trouble localizing it. Thx!
Hi @edz-o et al.,
I could not find details of banks in either the manuscript & supp. Could you elaborate or direct some materials on this? Thx
Hi @edz-o @Angtian @AdamKortylewski et al.,
Could u kindly provide hints on where the NLL loss is computed during training? The loss computation is a bit complicated, and I got confused. Thx!
3DNBF/mmhuman3d/models/losses/coke_loss.py
Line 464 in 3f9e868
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