3260 papers • 126 benchmarks • 313 datasets
Involves the task of predicting photorealistic pixel colors from feature buffers. Image source: Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
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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 is introduced, enabling training of high-quality neural graphics primitives in a matter of seconds, and rendering in tens of milliseconds at a resolution of 1920×1080.
This work presents a real-time neural radiance caching method for path-traced global illumination, and employs self-training to provide low-noise training targets and simulate infinite-bouncing transport by merely iterating few-bounce training updates.
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