Feb 12, 2022 · Abstract: Real-time Monte Carlo denoising aims at removing severe noise under low samples per pixel (spp) in a strict time budget.
Jul 15, 2021 · Real-time Monte Carlo denoising aims at removing severe noise under low samples per pixel (spp) in a strict time budget.
Ours 6-layer represents the 6-layer convolutional neural network architecture and Ours 3-layer represents the 3-layer convolutional neural network architecture.
Real-time Monte Carlo denoising aims at removing severe noise under low samples per pixel (spp) in a strict time budget. Recently, kernel-prediction methods use ...
Our experimental results demonstrate that this approach can robustly denoise 1-spp noisy input images at real-time frame rates (a few milliseconds per frame).
Sep 11, 2024 · Real-time Monte Carlo denoising aims at removing severe noise under low samples per pixel (spp) in a strict time budget.
Feb 29, 2024 · Fan et al. [8] employed a kernel prediction network that is called Weight Sharing Kernel Prediction Network (WSKPN). In order to reduce the ...
Real-time Monte Carlo denoising aims at removing severe noise under low samples per pixel (spp) in a strict time budget. Recently, kernel-prediction methods use ...
Deep Compositional Denoising for High-quality Monte Carlo Rendering Paper ... Real-time Monte Carlo Denoising with Weight Sharing Kernel Prediction Network ...
Regression-based algorithms have shown to be good at denoising Monte Carlo (MC) renderings by leveraging its inexpensive by-products (e.g., feature buffers) ...