Publications
Publications
DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer
Wenzheng Chen,
Joey Litalien,
Jun Gao,
Zian Wang,
Clément Fuji Tsang,
Sameh Khamis,
Or Litany,
and
Sanja Fidler
Neural Information Processing Systems
(NeurIPS),
December 2021
Neural Geometric Level of Detail: Real-time Rendering with Implicit 3D Shapes
Towaki Takikawa,
Joey Litalien,
Kangxue Yin,
Karsten Kreis,
Charles Loop,
Derek Nowrouzezahrai,
Alec Jacobson,
Morgan McGuire,
and
Sanja Fidler
Computer Vision and Pattern Recognition
(CVPR),
January 2021
Delayed Rejection Metropolis Light Transport
Damien Rioux-Lavoie,
Joey Litalien,
Adrien Gruson,
Toshiya Hachisuka,
and
Derek Nowrouzezahrai
ACM Transactions on Graphics
(Presented at SIGGRAPH),
May 2020
Other Projects
Online Test Suite for Rendering Research
A web comparison tool for rendering research written in Python+JS, based on the online test suite with interactive viewer by Disney Research. Useful for assembling supplementary material (comparison metrics, convergence plots, etc.)
Noise2Noise PyTorch Implementation
Unofficial PyTorch implementation of Noise2Noise: Learning Image Restoration without Clean Data by Lehtinen et al., 2018
Reproducing L2HMC
ICLR 2018 Reproducibility Challenge for Generalizing Hamiltonian Monte Carlo with Neural Networks by Lévy et al.
CelebA GANs
Implementation of different generative adversarial networks in PyTorch for small CelebA face generation.