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Fabrice Rousselle
Fabrice Rousselle
Senior Research Scientist, NVIDIA Research
Verified email at nvidia.com - Homepage
Title
Cited by
Cited by
Year
Neural importance sampling
T Müller, B McWilliams, F Rousselle, M Gross, J Novák
ACM Transactions on Graphics (ToG) 38 (5), 1-19, 2019
3312019
Kernel-predicting convolutional networks for denoising Monte Carlo renderings.
S Bako, T Vogels, B McWilliams, M Meyer, J Novák, A Harvill, P Sen, ...
ACM Trans. Graph. 36 (4), 97:1-97:14, 2017
3272017
Recent advances in adaptive sampling and reconstruction for Monte Carlo rendering
M Zwicker, W Jarosz, J Lehtinen, B Moon, R Ramamoorthi, F Rousselle, ...
Computer graphics forum 34 (2), 667-681, 2015
2132015
Denoising with kernel prediction and asymmetric loss functions
T Vogels, F Rousselle, B McWilliams, G Röthlin, A Harvill, D Adler, ...
ACM Transactions on Graphics (TOG) 37 (4), 1-15, 2018
1862018
Adaptive rendering with non-local means filtering
F Rousselle, C Knaus, M Zwicker
ACM Transactions on Graphics (TOG) 31 (6), 1-11, 2012
1512012
Adaptive sampling and reconstruction using greedy error minimization
F Rousselle, C Knaus, M Zwicker
ACM Transactions on Graphics (TOG) 30 (6), 1-12, 2011
1432011
Robust denoising using feature and color information
F Rousselle, M Manzi, M Zwicker
Computer Graphics Forum 32 (7), 121-130, 2013
1172013
Nonlinearly weighted first‐order regression for denoising Monte Carlo renderings
B Bitterli, F Rousselle, B Moon, JA Iglesias‐Guitián, D Adler, K Mitchell, ...
Computer Graphics Forum 35 (4), 107-117, 2016
1122016
Real-time neural radiance caching for path tracing
T Müller, F Rousselle, J Novák, A Keller
arXiv preprint arXiv:2106.12372, 2021
1032021
Denoising Monte Carlo renderings using machine learning with importance sampling
T Vogels, F Rousselle, B McWilliams, M Meyer, J Novak
US Patent 10,572,979, 2020
732020
Recent advances in facial appearance capture
O Klehm, F Rousselle, M Papas, D Bradley, C Hery, B Bickel, W Jarosz, ...
Computer Graphics Forum 34 (2), 709-733, 2015
662015
Path‐space motion estimation and decomposition for robust animation filtering
H Zimmer, F Rousselle, W Jakob, O Wang, D Adler, W Jarosz, ...
Computer Graphics Forum 34 (4), 131-142, 2015
602015
Neural control variates
T Müller, F Rousselle, A Keller, J Novák
ACM Transactions on Graphics (TOG) 39 (6), 1-19, 2020
552020
Kernel-predicting convolutional neural networks for denoising
T Vogels, J Novák, F Rousselle, B McWilliams
US Patent 10,475,165, 2019
512019
Nerf‐tex: Neural reflectance field textures
H Baatz, J Granskog, M Papas, F Rousselle, J Novák
Computer graphics forum 41 (6), 287-301, 2022
432022
Denoising monte carlo renderings using progressive neural networks
T Vogels, F Rousselle, B McWilliams, M Meyer, J Novak
US Patent 10,607,319, 2020
392020
Image-space control variates for rendering
F Rousselle, W Jarosz, J Novák
ACM Transactions on Graphics (TOG) 35 (6), 1-12, 2016
352016
Denoising Monte Carlo renderings using generative adversarial neural networks
T Vogels, F Rousselle, B McWilliams, M Meyer, J Novak
US Patent 10,586,310, 2020
282020
Improved sampling for gradient-domain metropolis light transport
M Manzi, F Rousselle, M Kettunen, J Lehtinen, M Zwicker
ACM Transactions on Graphics (TOG) 33 (6), 1-12, 2014
272014
Denoising Monte Carlo renderings using neural networks with asymmetric loss
T Vogels, F Rousselle, J Novak, B McWilliams, M Meyer, A Harvill
US Patent 10,699,382, 2020
242020
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