wbhu / Tri-MipRF

Tri-MipRF: Tri-Mip Representation for Efficient Anti-Aliasing Neural Radiance Fields, ICCV'23 (Oral, Best Paper Finalist)
https://wbhu.github.io/projects/Tri-MipRF
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about the geo_feat_dim #5

Open RedemptYourself opened 1 year ago

RedemptYourself commented 1 year ago

Hi ,what an excellent work 我简单的将TriMipRF 里的geo_feat_dim和feature_dim提升到了31和32,在训练过程中没有出现问题,但是到达eval_step执行eval_img报错: image 将geo_feat_dim重新设置为15不会出现该问题,您是否有头绪?万分感谢

wbhu commented 1 year ago

It may be an issue of tinycudann, you may set a smaller value for Trainer.test_chunk_size to try it

aiyb1314 commented 1 year ago

I'm experiencing a similar situation, but it's caused by a sample point of 0. I'm not sure how you solved it? Any ideas on how to fix it please?

AI-slam commented 6 months ago

Referen

I also meet this problem, have you solved it?

Luh1124 commented 3 months ago

Not a network issue, it's because during testing, the synthetic data is at the center of the scene, causing the initial chunksize ray sampling to be invalid, as they might just be the first few lines of pixels, all of which are blank. You can simply skip these intervals. You can refer to:

https://github.com/nerfstudio-project/nerfacc/issues/222#issuecomment-1827261309 https://github.com/nerfstudio-project/nerfacc/issues/207#issuecomment-1653621720