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The results generated by the nerd dataset are poor #146
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Hello @HeptagramV , If the result from our provided configs for the nerd datasets, e.g., https://github.com/NVlabs/nvdiffrec/blob/main/configs/nerd_gold.json The following config with flexicubes produced decent results in my test today.
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Thank you very much for your project and response. I ran with the configuration you provided today and found that the exported grid still has poor performance. Is this because I need to adjust additional settings in the export section? |
I'm not sure what you are using for visualizing the model. Do the images dumped from the nvdiffrec renderer during training look ok? For visualization of the exported models, you need to carefully check that the coordinate frames, material textures and tangent space matches. We provide a script for this for blender in nvdiffrecmc, https://github.com/NVlabs/nvdiffrecmc#use-the-extracted-3d-models-in-blender and I think that should work also for nvdiffrec. |
Thank you for your prompt response. I am very grateful for your help! I am also puzzled that there is a significant difference between the output images and the exported mesh during the training process: in these images, the inner side of this object clearly does not have the rough part in the mesh I obtained, which is as smooth as the result you provided earlier; |
This is my result and configuration file. Does anyone know how to solve it or have the same problem as me???
{
"ref_mesh": "data/nerd/moldGoldCape_rescaled",
"isosurface" : "flexicubes",
"random_textures": true,
"iter": 5000,
"save_interval": 100,
"texture_res": [ 2048, 2048 ],
"train_res": [512, 512],
"batch": 8,
"learning_rate": [0.03, 0.01],
"dmtet_grid" : 128,
"mesh_scale" : 5,
"kd_min" : [0.03, 0.03, 0.03],
"kd_max" : [0.8, 0.8, 0.8],
"ks_min" : [0, 0.08, 0.0],
"ks_max" : [0, 1.0, 1.0],
"background" : "white",
"display" : [{"bsdf":"kd"}, {"bsdf":"ks"}, {"bsdf" : "normal"}],
"out_dir": "nerd_gold_flexi"
}
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