Our lab alumnus, Prof. Bochang Moon, participated in SIGGRAPH 2024, held in Denver from July 28 to August 1, and presented his research titled “Target-Aware Image Denoising for Inverse Monte Carlo Rendering.” This study addresses the noise issue that arises when inferring scene parameters through physically based differentiable rendering by developing a target-aware image denoiser. The research points out that using conventional image denoisers can lead to undesirable local minima due to denoising bias and proposes a new denoiser that incorporates target image information to overcome this limitation. By determining denoising weights through linear regression based on target images, this method enables more robust scene parameter inference in inverse rendering optimization.
