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.
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Publications
* indicates equal contribution
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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.
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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.
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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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