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[SIGGRAPH 2024] "EASI-Tex: Edge-Aware Mesh Texturing from Single Image", ACM Transactions on Graphics.

Home Page: https://sairajk.github.io/easi-tex/

License: Other

Shell 0.03% Python 93.92% Makefile 0.04% Dockerfile 0.11% MDX 5.90%
3d controlnet deep-learning ip-adapter machine-learning mesh stable-diffusion texture texture-synthesis texture-transfer

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easi-tex's Issues

[TESTING] Result for a little bit complicated mesh

As expected, since this texture generation pipeline has no way to ensure consistent texture generation across the different views, and it doesn't try to keep the lighting condition the same across the different views, so the result is rather messy and unusable:

2024-06-1116-07-00-ezgif.com-resize-video.mp4

Last year, I tried the similar workflow, but in addition to Canny ControlNet & IP-Adaptor, I used AnimateDiff as a mean to ensure consistent texture generation across the different views, and use Brightness ControlNet to keep the lighting condition the same across the different views.

Result is better but still takes long to generate & same parameters are not always gives good results.

Cammy_MVs_Final_00001.mp4

pip install mathutils failure

Mathutils is in Blender, right? When I use pip install, it prompts installation failure. May I ask if it is possible
Do I need to configure the blender path separately?

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