tencentyouturesearch / 3dfacereconstruction-lap Goto Github PK

Hi Zhang! Thanks for sharing your great work! Would you please provide the demo of multi input reconstruction? Also, the reconstructions of Asian faces looked not lifelike. Maybe because of the training dataset. So do you have plan to release the training code?

Just wonder when to release the paper

In the DEMO part, I cannot open the link "pretrained model", thus I can't download the model. Maybe it's because I cannot log in google drive ? Could you please give me some advice?

Could u give some hints about the form of Eq(3)? Why is the loss calculated this way, and how is it derived?

如题

感谢你的工作，为什么泛化能力这么差呀？

您好，我在复现您的论文时遇到了一些问题。
请问可以将补充文档开出来么？像松弛一致性损失和感知损失的超参和如何使用在论文中没有明确说明，CVPR的官方也没有找着补充文档。在demo中的networks，也未找着置信度网络的结构。

I get the following error when trying to run the model on the sample images provided.

Loading checkpoint from ./demo/checkpoint300.pth
Saving checkpoint to ./demo/checkpoint300_fix2.pth
Processing ./images/001.png
/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:2705: UserWarning: Default grid_sample and affine_grid behavior has changed to align_corners=False since 1.3.0. Please specify align_corners=True if the old behavior is desired. See the documentation of grid_sample for details.
warnings.warn("Default grid_sample and affine_grid behavior has changed "
Rendering video animations
Traceback (most recent call last):
File "demo.py", line 347, in
result_code = model.run(pil_im)
File "demo.py", line 252, in run
self.render_animation()
File "demo.py", line 256, in render_animation
b, h, w = self.canon_depth.shape
AttributeError: 'Demo' object has no attribute 'canon_depth'

It looks like the object of class Demo as defined in demo.py does not have the canon_depth attribute in the current version of the code.

Hi! Thank you very much for such a great work!

I have a question about training in the size of 256×256 mentioned in your paper. Based on unsuper3d framework, I find that a single rendering time (i.e., rendering warped_depth) for 256×256 takes ~0.48 s in one NVIDIA Tesla V100 GPU, meaning that it takes ~38 days to train for 30 epoch. So I want to know if you have adopted a special differentiable renderer or parallel rendering method to speed up.

Again thank you for your work, looking forward to your reply :>.

Hello,JesseZhang92 ！Does your project will disclose the code of the model part of the model, how does the two indicators of MAD, SIDE assessment? I am looking forward to your reply.Thanks!

Hey guys,

I made a colab notebook for this project.
I'm currently getting this error

Traceback (most recent call last): File "demo.py", line 341, in <module> model = Demo(args) File "demo.py", line 53, in __init__ self.renderer_mr = Renderer(cfgs, im_size=128) File "/content/3DFaceReconstruction-LAP/lap/renderer/renderer_mr.py", line 45, in __init__ self.inv_k_mat = torch.inverse(k_mat).unsqueeze(0) RuntimeError: CUDA error: invalid device function

How to fix this?

Here is a link to my notebook , you can make a copy and edit it

https://colab.research.google.com/drive/18tIkvLIaN-_v3sLW2ykkcLGpqxwRN13z?usp=sharing