CVM 2019 [Paper] [Project Page]
A deep Dual-Encoder network, used for denoising Monte Carlo renderings. The feature buffers and noisy image are generated from renderer. The feature buffers are firstly fused by a feature fusion sub-network to get a detail map, and then the detail map and noisy image are encoded by the feature encoder and HDR encoder respectively. Finally, the latent representation is decoded to reconstruct a clean image with skip connection from the Dual-Encoder.
$ git clone https://github.com/wbhu/DEMC.git
$ cd DEMC
$ conda env create -f env.yml
To be done …
- Add model definition
- Add test code
- Add pre-trained model