Journal
ACM TRANSACTIONS ON GRAPHICS
Volume 38, Issue 5, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3269978
Keywords
Path tracing; reconstruction; regression; real-time
Categories
Funding
- TUT Graduate School
- Emil Aaltonen Foundation
- Finnish Foundation for Technology Promotion
- Nokia Foundation
- Business Finland [40142/14]
- Academy of Finland [297548, 310411]
- ECSEL JU project FitOptiVis [783162]
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Path tracing produces realistic results including global illumination using a unified simple rendering pipeline. Reducing the amount of noise to imperceptible levels without post-processing requires thousands of samples per pixel (spp), while currently it is only possible to render extremely noisy 1 spp frames in real time with desktop GPUs. However, post-processing can utilize feature buffers, which contain noise-free auxiliary data available in the rendering pipeline. Previously, regression-based noise filtering methods have only been used in offline rendering due to their high computational cost. In this article we propose a novel regression-based reconstruction pipeline, called Blockwise Multi-Order Feature Regression (BMFR), tailored for path-traced 1 spp inputs that runs in real time. The high speed is achieved with a fast implementation of augmented QR factorization and by using stochastic regularization to address rank-deficient feature data. The proposed algorithm is 1.8x faster than the previous state-of-the-art real-time path-tracing reconstruction method while producing better quality frame sequences.
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