Input-Dependent Uncorrelated Weighting for Monte Carlo Denoising
Author:
Affiliation:
1. Gwangju Institute of Science and Technology, South Korea
2. Trinity College Dublin, Ireland
3. University of Waterloo, Canada
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3610548.3618177
Reference47 articles.
1. Deep combiner for independent and correlated pixel estimates
2. Jonghee Back, Binh-Son Hua, Toshiya Hachisuka, and Bochang Moon. 2022. Self-Supervised Post-Correction for Monte Carlo Denoising. In ACM SIGGRAPH 2022 Conference Proceedings (Vancouver, BC, Canada) (SIGGRAPH ’22). Article 18, 8 pages.
3. Kernel-predicting convolutional networks for denoising Monte Carlo renderings
4. Gradient-domain path reusing
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