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Xilong Zhou
Xilong Zhou
Postdoctoral Researcher
xzhou (at) mpi-inf (dot) mpg (dot) de
[Nov. 2025]
Research Interests
My research goal is to develop a controllable and robust generative framework capable of producing virtual worlds that are perceptually indistinguishable from the real world. Toward this goal, my work spans the intersection of generative AI, computer graphics/vision, and deep learning. In the past, my research focused on neural rendering, as well as material acquisition and generation. Recently, my work has primarily centered on Generative AI for Video and 3D Content.
In summary, my research interests include (but are not limited to):
In summary, my research interests include (but are not limited to):
- Neural Rendering, Inverse Rendering, Relighting, and Appearance Modeling/Editing
- Generative AI for Material, 3D Content, and Video
- Novel View Synthesis, and 3D Representation
Publications
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(* Equal Contribution)
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OLATverse: A Large-scale Real-world Object Dataset with Precise Lighting Control Xilong Zhou, Jianchun Chen*, Pramod Rao*, Timo Teufel, Linjie Lyu, Tigran Minasian, Oleksandr Sotnychenko, Xiao-Xiao Long, Marc Habermann, and Christian Theobalt. Preprint 2025[PDF] [Paper Page] -
Splat the Net: Radiance Fields with Splattable Neural Primitives Xilong Zhou*, Bao-Huy Nguyen*, Loïc Magne, Vladislav Golyanik, Thomas Leimkühler, and Christian Theobalt Preprint 2025[PDF] [Paper Page] -
RealMat: Realistic Materials with Diffusion and Reinforcement Learning Xilong Zhou, Pedro Figueiredo, Miloš Hašan, Valentin Deschaintre, Paul Guerrero, Yiwei Hu, and Nima Khademi Kalantari Preprint 2025[PDF] [Paper Page] -
3DPR: Single Image 3D Portrait Relighting with Generative Priors Pramod Rao, Xilong Zhou*, Abhimitra Meka*, Gereon Fox, Mallikarjun B R, Fangneng Zhan, Tim Weyrich, Bernd Bickel, Hanspeter Pfister, Wojciech Matusik, Thabo Beeler, Mohamed Elgharib, Marc Habermann, and Christian Theobalt SIGGRAPH ASIA 2025[PDF] [Paper Page] -
PanoDreamer: Optimization-Based Single Image to 360 3D Scene With Diffusion Avinash Paliwal, Xilong Zhou, Andrii Tsarov, and Nima Kalantari SIGGRAPH ASIA 2025[PDF] [Paper Page] -
HumanOLAT: A Large-Scale Dataset for Full-Body Human Relighting and Novel-View Synthesis Timo Teufel, Pulkit Gera, Xilong Zhou, Umar Iqbal , Pramod Rao, Jan Kautz, Vladislav Golyanik, and Christian Theobalt ICCV 2025[PDF] [Paper Page] -
RI3D: Few-Shot Gaussian Splatting With Repair and Inpainting Diffusion Priors Avinash Paliwal, Xilong Zhou, Wei Ye, Jinhui Xiong, Rakesh Ranjan, and Nima Kalantari ICCV 2025[PDF] [Paper Page] -
PhotoMat: A Material Generator Learned from Single Flash Photos Xilong Zhou, Miloš Hašan, Valentin Deschaintre, Paul Guerrero, Yannick Hold-Geoffroy, Kalyan Sunkavalli, and Nima Khademi Kalantari SIGGRAPH 2023[PDF] [Paper Page] -
A Semi-procedural Convolutional Material Prior Xilong Zhou, Miloš Hašan, Valentin Deschaintre, Paul Guerrero, Kalyan Sunkavalli, and Nima Khademi Kalantari CGF2023 (Eurographics 2023)[PDF] [Paper Page] -
Look-Ahead Training with Learned Reflectance Loss for Single-Image SVBRDF Estimation Xilong Zhou and Nima Khademi Kalantari SIGGRAPH ASIA 2022[PDF] [Paper Page] -
TileGen: Tileable, Controllable Material Generation and Capture Xilong Zhou, Miloš Hašan, Valentin Deschaintre, Paul Guerrero, Kalyan Sunkavalli, and Nima Khademi Kalantari SIGGRAPH ASIA 2022[PDF] [Paper Page] -
Adversarial Single-Image SVBRDF Estimation with Hybrid Training Xilong Zhou and Nima Khademi Kalantari Eurographics 2021[PDF] [Paper Page] -
Enhanced adsorption of anionic surfactants on negatively charged quartz sand grains treated with cationic polyelectrolyte complex nanoparticles Xilong Zhou, Jenn-Tai Liang, Corbin D. Andersen, Jiajia Cai, and Ying-Ying Lin Colloids and Surfaces A: Physicochemical and Engineering Aspects, September 2018[PDF]
Ph.D. Thesis
Towards Practical And Robust Material Acquisition and Generation
Xilong Zhou
Advised by Ergun Akleman and Nima Kalantari
Texas A&M University, August 2024
Datasets
OLAT Datasets: HumanOLAT, FaceOLAT and OLATverse.
Material Datasets: Large-scale real-world material surfaces under a single point light and a moving light source.
Material Datasets: Large-scale real-world material surfaces under a single point light and a moving light source.
Academic Service
Reviewer: SIGGRAPH, SIGGRAPH Asia, Eurographics, Pacific Graphics, ICCV, TOG, IEEE TVCG, IEEE TPAMI, CGF, Computers & Graphics.
Teaching
Co-Instructor: Graphics and AI Seminar, Saarland University
Summer 2025
Teaching Assistant: Analysis of Algorithms, Texas A&M University
Fall 2021, Summer 2019
Teaching Assistant: Machine Learning, Texas A&M University
Spring 2022, Fall 2020
Teaching Assistant: Programming, Texas A&M University
Spring 2021
Teaching Assistant: Discrete Structures for Computing, Texas A&M University
Fall 2019, Fall 2018
Teaching Assistant: Data Structures and Algorithms, Texas A&M University
Spring 2019
Teaching Assistant: Computers for Visualization, Texas A&M University
Summer/Spring 2017
Teaching Assistant: Formation Evaluation, Texas A&M University
Spring 2016
Teaching Assistant: Unconventional Oil and Gas, Texas A&M University
Fall 2015
Selected Awards
Travel Grant, CSCE Department, Texas A&M University
2023
National First Prize of National Petroleum Engineering Design Competition
2013
Honorable Mention of Mathematical Contest in Modeling
2013
National Second Prize of National Mathematics Modeling Contest
2012
Misc
Art: I like painting. You can find some of my artworks from this Portfolio link.
Animation: I have ever made a short animation from scratch using Maya, "Pokeman Go Go Ghost"
Sport: I enjoy hiking, running, playing soccer, and gym
Animation: I have ever made a short animation from scratch using Maya, "Pokeman Go Go Ghost"
Sport: I enjoy hiking, running, playing soccer, and gym