Xiaoyan Xing (邢晓岩)

I am a second-year ELLIS PhD candidate at Delta Lab, a lab funded by Bosch and University of Amsterdam, where 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 and Dr. Konrad Groh.

Prior to that, I obtained my master's degree (MSc) from Tsinghua University and my bachelor's degree (BEng) from Chongqing University, both in Biomedical Engineering.

I am a photography enthusiast 📸, I play the drum in a rock band 🥁, and I also like traveling (4 continents unlocked, 3 more to go) 🗺️.

I serve as a regular reviewer for CVPR, ECCV, NeurIPS, ICLR, and IJCV.

I am actively looking for motivated students from UvA, who have hands-on experience in computer vision, to explore some interesting tasks with me (with compensation). Feel free to drop your resume to my Email.

Email  /  Linkedin  /  Google Scholar  /  Github

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.

Real-world indoor scene image-based relighting without inverse rendering.

Diffusion models "know" the illumination, and we show how to control it.

Point cloud based intrinsic appearance decomposition achieves good accuracy and can be generalized to unseen scenes/shapes.

Point cloud is an ideal form that contains color and depth information and can be used to improve illumination estimation pipline.

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.

This website is based on Jon's source code.