Bowei Chen （陈柏维）

I am a Ph.D. student at University of Washington, working with Prof. Steve Seitz, Prof. Brian Curless, and Prof. Ira Kemelmacher-Shlizerman.

Previously, I was an MSR student in Robotics Institute at Carnegie Mellon University, supervised by Prof. Srinivasa Narasimhan. I also worked with Prof. Martial Hebert, Dr. Sing Bing Kang, and Dr. Tiancheng Zhi.

I did my bachelors at Northeastern University , where I worked with Prof. Jean-François Lalonde, Prof. Guibing Guo, and Dr. Fajie Yuan.

Email  /  CV  /  Google Scholar  /  Github

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Research

My research interests lie at the intersection of computer vision and graphics, including neural rendering, inverse rendering and 3D reconstruction. Previously, I worked on developing recommender systems methods.

Publications

* indicates equal contribution

dise Learning Continuous Implicit Representation for Near-Periodic Patterns.
Bowei Chen, Tiancheng Zhi, Martial Hebert, Srinivasa Narasimhan.
ECCV 2022
[Arxiv] [Paper] [Website] [Video] [Poster] [Supp] [Code]

Present a periodicity-aware framework to learn Near-Periodic Patterns (NPP) representation, which enables various applications including NPP completion, resolution-enhanced remapping, and segmentation.
dise Semantically Supervised Appearance Decomposition for Virtual Staging from a Single Panorama.
Tiancheng Zhi, Bowei Chen, Ivaylo Boyadzhiev, Sing Bing Kang, Martial Hebert, Srinivasa Narasimhan.
SIGGRAPH 2022
[Paper] [Website] [Code]

Present a weakly supervised appearance decomposition for a single indoor panorama. The applications include furniture insertion, sunlight direction changing, and floor material changing.

dise Leveraging Title-Abstract Attentive Semantics for Paper Recommendation
Guibing Guo, Bowei Chen, Xiaoyan Zhang, Zhirong Liu, Zhenhua Dong, Xiuqiang He.
AAAI 2020
[paper]

Propose a two-level attentive neural network to capture title-abstract semantics relationships for paper recommendation.

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