Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
description [Jan 19th 2022] Paper released on arXiv. integration_instructions [Jan 14th 2022] Code released on GitHub. Neural graphics primitives, parameterized by fully connected neural networks, can be costly to train and evaluate. We reduce this cost with a versatile new input encoding that permits the use of a smaller network without sacrificing quality, thus significantly reducing the number of floating point and memory access operations.
https://nvlabs.github.io/instant-ngp/
Seonglae Cho
