More Like this

1. Neural Neural Textures Make Sim2Real Consistent

   Burgert, Ryan; Shang, Jinghuan; Li, Xiang; Ryoo, Michael S. (December 2022, Conference on Robot Learning (CoRL))
2. Neural Spike Sorting Using Binarized Neural Networks

   https://doi.org/10.1109/TNSRE.2020.3043403  

   Valencia, Daniel; Alimohammad, Amir (January 2021, IEEE Transactions on Neural Systems and Rehabilitation Engineering)
3. A generic neural network model to estimate populational neural activity for robust neural decoding

   https://doi.org/10.1016/j.compbiomed.2022.105359  

   Roy, Rinku; Xu, Feng; Kamper, Derek G.; Hu, Xiaogang (May 2022, Computers in Biology and Medicine)
4. NeuTex: Neural Texture Mapping for Volumetric Neural Rendering

   Xiang, Fanbo; Xu, Zexiang; Hasan, Milos; Hold-Geoffroy, Yannick; Sunkavalli, Kalyan; Su, Hao (January 2021, IEEE Conference on Computer Vision and Pattern Recognition)

   null (Ed.)
5. Neural radiosity

   https://doi.org/10.1145/3478513.3480569  

   Hadadan, Saeed; Chen, Shuhong; Zwicker, Matthias (December 2021, ACM Transactions on Graphics)

   We introduce Neural Radiosity, an algorithm to solve the rendering equation by minimizing the norm of its residual, similar as in classical radiosity techniques. Traditional basis functions used in radiosity, such as piecewise polynomials or meshless basis functions are typically limited to representing isotropic scattering from diffuse surfaces. Instead, we propose to leverage neural networks to represent the full four-dimensional radiance distribution, directly optimizing network parameters to minimize the norm of the residual. Our approach decouples solving the rendering equation from rendering (perspective) images similar as in traditional radiosity techniques, and allows us to efficiently synthesize arbitrary views of a scene. In addition, we propose a network architecture using geometric learnable features that improves convergence of our solver compared to previous techniques. Our approach leads to an algorithm that is simple to implement, and we demonstrate its effectiveness on a variety of scenes with diffuse and non-diffuse surfaces. 

   more » « less