Fujun Luan

I am a research scientist at Adobe Research. I received my Ph.D. from Cornell University in 2021, under the supervision of Prof. Kavita Bala. Before that, I obtained my bachelor degree from Tsinghua University in 2015, advised by Prof. Kun Xu.

Now, I focus on inverse graphics, differentiable rendering, and neural rendering.

[ Email ] [ Google Scholar ] [ GitHub ] [ LinkedIn ] [ CV ] [ Photos ]

Publications

PaletteNeRF: Palette-based Appearance Editing of Neural Radiance Fields
Zhengfei Kuang, Fujun Luan, Sai Bi, Zhixin Shu, Gordon Wetzstein, Kalyan Sunkavalli

arXiv 2022 [ Project ] [ arXiv ]

Differentiable Rendering using RGBXY Derivatives and Optimal Transport
Jiankai Xing, Fujun Luan, Ling-Qi Yan, Xuejun Hu, Houde Qian, Kun Xu

SIGGRAPH Asia 2022 [ Project ] [ Paper ] [ Supplementary ] [ Code ]

Learning-based Inverse Rendering of Complex Indoor Scenes with Differentiable Monte Carlo Raytracing
Jingsen Zhu, Fujun Luan, Yuchi Huo, Zihao Lin, Zhihua Zhong, Dianbing Xi, Jiaxiang Zheng, Rui Tang, Hujun Bao, Rui Wang

SIGGRAPH Asia 2022 [ Project ] [ Paper ] [ Supplementary ]

Differentiable Rendering of Neural SDFs through Reparameterization
Sai Praveen Bangaru, Michaël Gharbi, Tzu-Mao Li, Fujun Luan, Kalyan Sunkavalli, Miloš Hašan, Sai Bi, Zexiang Xu, Gilbert Bernstein, Frédo Durand

SIGGRAPH Asia 2022 [ Project ] [ Paper ]

ARF: Artistic Radiance Fields
Kai Zhang, Nick Kolkin, Sai Bi, Fujun Luan, Zexiang Xu, Eli Shechtman, Noah Snavely

ECCV 2022 [ Project ] [ Paper ]
This work was demoed at Adobe MAX Sneaks 2022 as Artistic Scenes.

Reconstructing Translucent Objects using Differentiable Rendering
Xi Deng, Fujun Luan, Bruce Walter, Kavita Bala, Steve Marschner

SIGGRAPH 2022 [ Project ] [ Paper ] [ Supplementary ]

Rendering Neural Materials on Curved Surfaces
Alexandr Kuznetsov, Xuezheng Wang, Krishna Mullia, Fujun Luan, Zexiang Xu, Miloš Hašan, Ravi Ramamoorthi

SIGGRAPH 2022 [ Project ] [ Paper ]

IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images
Kai Zhang, Fujun Luan, Zhengqi Li, Noah Snavely

CVPR 2022 (oral) [ Project ] [ Paper ] [ Video ] [ Supplementary ] [ arXiv ]

Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Rendering
Fujun Luan, Shuang Zhao, Kavita Bala, Zhao Dong

EGSR 2021 [ Project ] [ Paper ] [ Video ] [ Supplementary ] [ arXiv ]

PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting
Kai Zhang^*, Fujun Luan^*, Qianqian Wang, Kavita Bala, Noah Snavely (* equal contribution)

CVPR 2021 [ Project ] [ Paper ] [ Video ] [ Poster ] [ Code & Data ]

Langevin Monte Carlo Rendering with Gradient-based Adaptation
Fujun Luan, Shuang Zhao, Kavita Bala, Ioannis Gkioulekas

SIGGRAPH 2020 [ Project ] [ Paper ] [ Supplementary ] [ Interactive Test Suite ] [ Code & Data ]

Towards Learning-based Inverse Subsurface Scattering
Chengqian Che, Fujun Luan, Shuang Zhao, Kavita Bala, Ioannis Gkioulekas

ICCP 2020 [ Project ] [ Paper ] [ Video ] [ Supplementary ] [ Code & Data ]

Deep Painterly Harmonization
Fujun Luan, Sylvain Paris, Eli Shechtman, Kavita Bala

EGSR 2018 [ Paper ] [ Video ] [ arXiv ] [ GitHub (6.1k stars) ]
Press coverage: Vice, IFLScience, Filo.news, slashCAM, 雷锋网, Onedio, 이웃집과학자, N+1, 量子位, Two Minute Papers.

Fiber-Level On-the-Fly Procedural Textiles
Fujun Luan, Shuang Zhao, Kavita Bala

EGSR 2017 [ Project ] [ Paper ] [ Video ] [ Slides ] [ 4K Rendering ]

Deep Photo Style Transfer
Fujun Luan, Sylvain Paris, Eli Shechtman, Kavita Bala

CVPR 2017 [ Project ] [ Paper ] [ Supplementary ] [ arXiv ] [ GitHub (9.9k stars) ] [ Poster ]
Press coverage: The Verge, PetaPixel, DPreview, SlashGear, AppleInsider, Digital Trends, BGR, Lifeboat, Engadget, New Atlas, TNW, TechSpot, Ubergizmo, Softpedia, Cornell Chronicle, ExtremeTech, Phys.org, Two Minute Papers.

Fitting Procedural Yarn Models for Realistic Cloth Rendering
Shuang Zhao, Fujun Luan, Kavita Bala

SIGGRAPH 2016 [ Project ] [ Paper ] [ Video ] [ Slides ] [ Code & Data ]
This work was patented as U.S. Patent No. 10,410,380.