https://sgvr.kaist.ac.kr/publication/target-aware-image-denoising-for-inverse-monte-carlo-rendering/
TopACM Transactions on Graphics (SIGGRAPH 2024), 2024
Physically based differentiable rendering allows an accurate light transport simulation to be differentiated with respect to the rendering input, i.e., scene parameters, and it enables inferring scene parameters from target … Continue reading "Target-Aware Image Denoising for Inverse Monte Carlo Rendering"
https://sgvr.kaist.ac.kr/publication/weakly-supervised-contrastive-learning-in-path-manifold-for-monte-carlo-image-reconstruction/
TopACM Trans. on Graphics (ToG) (proc. of SIGGRAPH), 2021
https://sgvr.kaist.ac.kr/publication/adaptive-incident-radiance-field-sampling-and-reconstruction-using-deep-reinforcement-learning/
TopACM Trans. on Graphics (ToG), 2020
https://sgvr.kaist.ac.kr/publication/adaptive-rendering-with-linear-predictions/
TopACM Transaction on Graphics (Proc. of SIGGRAPH), 2015