Comments (4)
@ThumbmasWalker Not sure which figure are you referring to. But AtlasNet produces a UV parameterization by construction: each 3D point was mapped from some 2D location. If you store these 2D locations as UV coordinates, in, say, OBJ file, you can apply any kind of material to it, including a checkerboard texture. You can simply add material header to OBJ file and manually create corresponding MTL file that references a 2D texture of your choice.
We also visualize optimized UV maps after distortion minimization. For this, I would just use off-the-shelf geometric optimization (e.g., SLIM: https://github.com/MichaelRabinovich/Scalable-Locally-Injective-Mappings ) to get better UVs.
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@vokim may be able to help
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Thanks for the reply this is really helpful (I am coming from a machine learning background rather than a CG background so this is quite new to me). Are there any programs you would recommend to create the mtl file? Thanks again.
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Don't worry, think I've figured it out!
All the best,
Tom
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Related Issues (20)
- (Meshlab Visualization Trick ) Parts of faces flipped in the generated obj by train.py --demo HOT 1
- V2.2 dataset links are invalid (not the ones from V1) HOT 2
- some data download questions HOT 8
- Strangley poor results on pre-trained model HOT 6
- the pretrained resenet model under shapenet HOT 2
- Question about data HOT 2
- AtlasNet checkpoint not available HOT 5
- Question about train and test strategy HOT 2
- pymesh library HOT 1
- Compile Metro Distance (GPL3 Licence) HOT 1
- Question About Visulization HOT 2
- Weird results using pre-trained model HOT 1
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- Unable to find normalised mesh dataset in AtlasNetv2 HOT 3
- test HOT 3
- Learning representations for pointcloud manifold
- Cannot Load autoencoder_25_squares & Poor Performance on Pre-trained Model HOT 1
- AttributeError: module 'torch._C' has no attribute '_cuda_setDevice' HOT 4
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