Yue Chen (陈悦)

I obtained my Master’s degree from the Institute of Artificial Intelligence and Robotics at Xi’an Jiaotong University in 2022, supervised by Prof. Fei Wang and Prof.Yu Guo. I did my undergrad at Xiamen University.

During my master, I was a research intern in Visual Computing Center at Tencent AI lab, working with Jue Wang and Xuan Wang.

I am a Muggle dreaming of the Wizarding World. Luckily, I can create magic via neural fields and a closed loop formed by computer vision and computer graphics between 2D images and the 3D world!

Email  |  Google Scholar  |  GitHub

headshot
News
  • 03/2023 I am actively looking for a Ph.D. position. If possible, please email me for further communication!
  • 02/2023 2 papers (L2G-NeRF, UV Volumes) accepted to CVPR 2023!
  • 01/2023 1 paper (PROCA) accepted to ICRA 2023!
  • 03/2022 1 paper (Ha-NeRF) accepted to CVPR 2022!
Research

Equal Contribution * , Corresponding Author †

L2G-NeRF: Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields
Yue Chen*, Xingyu Chen*, Xuan Wang†, Qi Zhang, Yu Guo†, Ying Shan, Fei Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
project page / arXiv / code / video

A Local-to-Global robust registration strategy for bundle-adjusting Neural Radiance Fields, combining the global and local alignment via differentiable parameter estimation.
UV Volumes for Real-time Rendering of Editable Free-view Human Performance
Yue Chen*, Xuan Wang*, Xingyu Chen, Qi Zhang, Xiaoyu Li, Yu Guo†, Jue Wang, Fei Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023
project page / arXiv / code / supplementary / video

The first deformable, real-time rendering, and editable NeRF, decomposing a dynamic human into 3D UV Volumes and a 2D appearance texture.
PROCA: Place Recognition under Occlusion and Changing Appearance via Disentangled Representations
Yue Chen, Xingyu Chen†, Yicen Li
IEEE International Conference on Robotics and Automation (ICRA), 2023
arXiv / code / video / poster

An unsupervised approach to disentangle a scene into place, appearance, and occlusion features, where the place feature significantly increases the recall of place recognition under occlusion and changing appearance.

Ha-NeRF😆: Hallucinated Neural Radiance Fields in the Wild
Xingyu Chen, Qi Zhang†, Xiaoyu Li, Yue Chen, Ying Feng, Xuan Wang, Jue Wang
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
project page / arXiv / paper / code / supplementary / video / poster

A framework to recover hallucinated neural radiance fields from tourism images with variable appearance and occlusions, consistently rendering free-occlusion views under different appearance hallucinations.

Projects
Deformation Field Estimation Using Fiber Bragg Grating Sensors
Yue Chen, Hu Sun
Xiamen University Outstanding Undergraduate Thesis Award, 2019

A study on deformation field estimation for the wing physical model using the Fiber Bragg Grating sensing network, which can be applied in aerospace structural health monitoring.


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Last updated: Mar 2023