Fabrice Rousselle
Most Recent Affiliation(s):
- Disney Research and NVIDIA
Learning Category: Presentation(s):
![Inverse Global Illumination Using a Neural Radiometric Prior](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Hadadan_Inverse-Global-Illumination-using-a-Neural-Radiometric-Prior-02-150x150.jpg)
Type: [Technical Papers]
Inverse Global Illumination Using a Neural Radiometric Prior Presenter(s): [Hadadan] [Lin] [Novák] [Rousselle] [Zwicker]
[SIGGRAPH 2023]
![Recursive Control Variates for Inverse Rendering](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Nicolet_Recursive-Control-Variates-for-Inverse-Rendering-150x150.jpg)
Type: [Technical Papers]
Recursive Control Variates for Inverse Rendering Presenter(s): [Nicolet] [Rousselle] [Novák] [Keller] [Jakob] [Müller]
[SIGGRAPH 2023]
![Neural scene graph rendering](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Granskog_Neural-Scene-Graph-Rendering-150x150.jpg)
Type: [Technical Papers]
Neural scene graph rendering Presenter(s): [Granskog] [Schnabel] [Rousselle] [Novák]
[SIGGRAPH 2021]
![Real-time neural radiance caching for path tracing](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Muller_Real-time-Neural-Radiance-Caching-for-Path-Tracing-150x150.jpg)
Type: [Technical Papers]
Real-time neural radiance caching for path tracing Presenter(s): [Müller] [Rousselle] [Novák] [Keller]
[SIGGRAPH 2021]
![Compositional Neural Scene Representations for Shading Inference](https://history.siggraph.org/wp-content/uploads/2023/02/2020-Technical-Papers-Granskog_Compositional-Neural-Scene-Representaitons-for-Shading-Inference-150x150.jpg)
Type: [Technical Papers]
Compositional Neural Scene Representations for Shading Inference Presenter(s): [Granskog] [Rousselle] [Papas] [Novák]
[SIGGRAPH 2020]
![Neural Importance Sampling](https://history.siggraph.org/wp-content/uploads/2022/07/2019-SIGGRAPH-Image-Not-Available-150x150.jpg)
Type: [Technical Papers]
Neural Importance Sampling Presenter(s): [Müller] [Mcwilliams] [Rousselle] [Gross] [Novák]
[SIGGRAPH 2019]
![Denoising with kernel prediction and asymmetric loss functions](https://history.siggraph.org/wp-content/uploads/2023/02/2018-Technical-Papers-Vogels_Denoising-with-Kernel-Prediction-and-Asymmetric-Loss-Functions-150x150.jpg)
Type: [Technical Papers]
Denoising with kernel prediction and asymmetric loss functions Presenter(s): [Vogels] [Rousselle] [Mcwilliams] [Röthlin] [Harvill] [Adler] [Meyer] [Novák]
Entry No.: [124]
[SIGGRAPH 2018]
Role(s):
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