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I am currently a student researcher at Google DeepMind in San Francisco. I am a third year ELLIS PhD candidate at (UvA-Bosch) Delta Lab, part of the Amsterdam Machine Learning Lab and the Computer Vision Research Group at the University of Amsterdam. I am working on computer vision and machine learning, and am supervised by Prof. Dr. Theo Gevers. I am also very glad to work with Dr. Anand Bhattad. Prior to that, I obtained my master's degree (MSc) from Tsinghua University and my bachelor's degree (BEng) from Chongqing University. I am a photography enthusiast πΈ, I play the drum in a rock band π₯, and I also like traveling (4 continents unlocked, 3 more to go) πΊοΈ. I am open to collaborations in the context of intrinsic images, relighting, and color constancy. Feel free to send me an email! Email / Linkedin / Google Scholar / Github |
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[Aug 2025] I started my internship at GDM! [Feb 2025] LumiNet is accepted by CVPR 2025. The Demo released! [Jun 2024] I gave an invited talk @ PBDL workshop, CVPR 2024. [Oct 2023] I gave a contributed talk @ CV4Metaverse workshop, ICCV 2023. [Jul 2023] I participated ICVSS 2023 in Sicily! [February 2023] I was nominated as an ELLIS PhD! [September 2022] I started my PhD adventure 🤞! [August 2022] I arrived in the Netherlands! [June 2022] I graduated with a Master's degree (MSc) from Tsinghua University. [April 2022] I will start my Ph.D. journey in computer vision at Delta Lab (funded by Bosch), University of Amsterdam, supervised by prof. dr. Theo Gevers. [March 2022] One paper was accepted by CVPR 2022! [March 2022] One paper was accepted by ICPR 2022! (early accepted) |
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Photography is known as the art of illumination and color, in which I have a great interest. My research focuses on understanding lighting and the intrinsic properties of the physical world through images, with a particular emphasis on applications such as relighting. |
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Xiaoyan Xing, Konrad Groh, Sezer Karaoglu, Theo Gevers, Anand Bhattad CVPR 2025 arxiv / website / Code / Demo Real-world indoor scene image-based relighting without inverse rendering. |
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Xiaoyan Xing, Vincent Tao Hu, Jan Hendrik Metzen, Konrad Groh, Sezer Karaoglu, Theo Gevers Invited talk @ PBDL, CVPR 2024 arxiv Diffusion models "know" the illumination, and we show how to control it. |
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Xiaoyan Xing, Konrad Groh, Sezer Karaoglu, Theo Gevers CV4Metaverse Workshop, ICCV 2023 (Oral) arxiv / workshop (4 pages) / code Point cloud based intrinsic appearance decomposition achieves good accuracy and can be generalized to unseen scenes/shapes. |
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Xiaoyan Xing, Yanlin Qian, Sibo Feng, Yuhan Dong, Jiri Matas CVPR, 2022 paper / code / data Point cloud is an ideal form that contains color and depth information and can be used to improve illumination estimation pipline. |
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Xiaoyan Xing, Sibo Feng, Yanlin Qian, Yuhan Dong ICPR, 2022 paper Efficient RAW dual-Illumination image generation using a random gaussian map and guided filter helps the network to estimate illumination map of unseen dual-illuminant images. |
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Teaching asistant, Big Data Experiment and Application Spring 2021 Teaching asistant, Public Health Statistics Spring 2020 |
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This website is based on Jon's source code. |