Accelerating Neural Field Training via Soft Mining
Shakiba Kheradmand, Daniel Rebain, Gopal Sharma, Hossam Isack, Abhishek Kar, Andrea Tagliasacchi, Kwang Moo Yi
摘要
https://ubc-vision.github.io/nf-soft-mining/ Figure 1. Teaser: we introduce "soft mining" to accelerate neural field training. When applied to Neural Radiance Field (NeRF) training, our method significantly improves convergence. We visualize the error maps (blue denotes low error and red denotes high error) and the rendered novel views for uniform sampling and our method. We plot the convergence showing the Peak Signal-to-Noise Ratio (PSNR) for the corresponding scene. We render both images at 1k iterations of training, specified by the red dashed line in the (right) graph. Our method achieves the same PSNR significantly faster than the baselines.
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引用它的顶会 Paper7
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它引用的顶会 Paper21
- 3D Gaussian Splatting for Real-Time Radiance Field RenderingBernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George DrettakisSIGGRAPH 2023 · 被引用 5,687 次
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