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Delio Vicini
Title
Cited by
Cited by
Year
Mitsuba 2: A retargetable forward and inverse renderer
M Nimier-David, D Vicini, T Zeltner, W Jakob
ACM Transactions on Graphics (ToG) 38 (6), 1-17, 2019
4492019
Mitsuba renderer
W Jakob, S Speierer, N Roussel, M Nimier-David, D Vicini, T Zeltner, ...
4332010
Dr. Jit: a just-in-time compiler for differentiable rendering
W Jakob, S Speierer, N Roussel, D Vicini
ACM Transactions on Graphics (TOG) 41 (4), 1-19, 2022
802022
Differentiable Signed Distance Function Rendering
D Vicini, S Speierer, W Jakob
ACM Transactions on Graphics (TOG) 41 (4), 1-18, 2022
782022
Path replay backpropagation: Differentiating light paths using constant memory and linear time
D Vicini, S Speierer, W Jakob
ACM Transactions on Graphics (TOG) 40 (4), 1-14, 2021
692021
Mitsuba 3 renderer, 2022
W Jakob, S Speierer, N Roussel, M Nimier-David, D Vicini, T Zeltner, ...
URL: https://mitsuba-renderer. org 7, 0
44
A learned shape-adaptive subsurface scattering model
D Vicini, V Koltun, W Jakob
ACM Transactions on Graphics (TOG) 38 (4), 1-15, 2019
432019
A non-exponential transmittance model for volumetric scene representations
D Vicini, W Jakob, A Kaplanyan
ACM Transactions on Graphics (TOG) 40 (4), 1-16, 2021
272021
Denoising deep monte carlo renderings
D Vicini, D Adler, J Novák, F Rousselle, B Burley
Computer Graphics Forum 38 (1), 316-327, 2019
222019
Regularizing image reconstruction for gradient‐domain rendering with feature patches
M Manzi, D Vicini, M Zwicker
Computer graphics forum 35 (2), 263-273, 2016
192016
Renderer. 2022
W Jakob, S Speierer, N Roussel, M Nimier-David, D Vicini, T Zeltner, ...
URL: https://mitsubarenderer. org, 3
113
Solving Inverse PDE Problems using Grid-Free Monte Carlo Estimators
EF Yılmazer, D Vicini, W Jakob
arXiv preprint arXiv:2208.02114, 2022
82022
LitNeRF: Intrinsic Radiance Decomposition for High-Quality View Synthesis and Relighting of Faces
K Sarkar, MC Bühler, G Li, D Wang, D Vicini, J Riviere, Y Zhang, ...
SIGGRAPH Asia 2023 Conference Papers, 1-11, 2023
62023
Efficient and Accurate Physically-Based Differentiable Rendering
DA Vicini
EPFL, 2022
12022
Denoising binned-depth images
DM Adler, DA Vicini, B Burley, J Novak, FPA Rousselle
US Patent 10,565,685, 2020
12020
Denoising Deep Monte Carlo Renderings.
D Adler, B Burley, D Vicini, J Novák, F Rousselle
Computer Graphics Forum 38 (1), 2019
2019
“Path replay backpropagation: differentiating light paths using constant memory and linear time” by Vicini, Speierer and Jakob
D Vicini
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Articles 1–17