NextFace
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A high-fidelity 3D face reconstruction library from monocular RGB image(s)
Hey there, thanks for your impressive work! I tried Nextface first and now implemented DeepNextFace by myself, using default resnet152 in pytorch(pretrained on ImageNet), but during step 1, landmark loss...
iterStep1 2000 left Deep3DFaceRecon_pytorch, right NextFace.    iterStep1 10000   
Thanks for your great works. I want to know the process of calculating uvParametrization.pickle, in order to replace BFM model to FLAME. Looking forward to your detailed answer.
Hi! Thanks for your code. I have some questions about smoothing SH coeffs. I notice that during optimization there is no `smoothSH` operation because the default value of smooth is...
Dear author, Thank you for the great work. During the reproducing process, I noticed that the rendering result is with eye balls, while the paper results do not have that....
Hi, I am new in the AI world and I am sorry for my ingnorance. The question that I have and (I have not found the reponse yet) is why...
Implementation of the following renderers - Mitsuba 3 another differentiable renderer - Vertex based Mitusba is a well documented ray tracing differentiable renderer that supports : - newer graphic cards...
Trying to run the replay.py animation but I'm getting the below error: ``` loading optim config from: ./optimConfig.ini Loading Basel Face Model 2017 from ./baselMorphableModel/morphableModel-2017.pickle... loading mesh normals... loading uv...
`(faceNext) C:\Users\aades\Music\testthings\NextFace>python optimizer.py --sharedIdentity --input C:\Users\aades\Downloads\face --output C:\Users\aades\Downloads\New\ loading optim config from: ./optimConfig.ini [WARN] no cuda enabled device found. switching to cpu... Loading Basel Face Model 2017 from ./baselMorphableModel/morphableModel-2017.pickle... loading...
win 11, 4090 ``` C:\NextFace\landmarksfan.py:35: UserWarning: Creating a tensor from a list of numpy.ndarrays is extremely slow. Please consider converting the list to a single numpy.ndarray with numpy.array() before converting...