lizhe00/posevocab

Code of [SIGGRAPH 2023] "PoseVocab: Learning Joint-structured Pose Embeddings for Human Avatar Modeling"

posevocab's Issues

Run on ZJU-MoCap Dataset

Will you provide the scripts about running on ZJU-MoCap?

question about dataset

Hi!!! This is a wonderful work!
And more, in your paper, you mentioned the following dataset:THuman4.0,DeepCap and ZJU-MoCap,but you only gave a description of how to use the THuman4.0 dataset. Will you publish the processing methods of other datasets, or will the other datasets be treated the same as the THuman 4.0 datasets?
Best wish!!

Python environment for the code

Hi @lizhe00 , thanks a lot for releasing the code!

Could you share the python environment for this repo?

hello, is the possible convert the input 3d keypoints to SMPL rotations?

hello, is the possible convert the input 3d keypoints to SMPL rotations?

Release Date

How soon will this model be released for learning

live_bounds parameter seems incorrect and cannot be correctly bound

Great job. I tried the CMU dataset and did SMPL fitting well, but during training, I couldn't do it. After checking, I found that live_ Bounds cannot be drawn correctly. Can you tell me what this is related to? Camera calibration?
my error：
File "/project-ssd/PoseVocab/dataset/dataset_mv_rgb_slrf.py", line 257, in getitem
nerf_random = nerf_util.sample_randomly_for_nerf_rendering(color_img, mask_img, depth_img, self.extr_mats[view_idx], self.intr_mats[view_idx], live_bounds, unsample_region_mask = boundary_mask_img, **ray_sampling['random'])
File "/project-ssd/PoseVocab/utils/nerf_util.py", line 293, in sample_randomly_for_nerf_rendering
sampled_inside_uv = inside_uv[np.random.choice(inside_uv.shape[0], inside_sample_num, replace = False)]
File "mtrand.pyx", line 909, in numpy.random.mtrand.RandomState.choice
ValueError: a must be greater than 0 unless no samples are taken

Inference time per frame

Hi, thank you for the awesome work! I would like to ask what is the inference time of it? Can it achieve real-time performance?

Question about the evaluation steps for the Tab.1

Dear author,

Thx for your great work about human avatar modeling. However, I con only find testing code in your repo. Could you pls tell the detailed steps/settings for your evaluation results in Tab.1? like, the frame ids and camera ids used to compute PSNR/SSIM/... for both training and novel poses.