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I am a Research Scientist at NetEase Fuxi AI Lab, working on 3D computer vision and content generation. I recieved my Master's degree from Zhejiang University, advised by Prof. Xi Li. Before that, I received my undergraduate degree in the CS Department, Zhejiang University in July 2018. My research interest lies at the intersection of computer vision and computer graphics. I am particularly excited about neural rendering, 3D reconstruction, differentiable rendering, montion capture and motion generation, etc. |
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[3] Haoqian Wu, Zhipeng Hu1,2, Lincheng Li, Yongqiang Zhang, Changjie Fan, Xin Yu CVPR, 2023 paper / project page We introduce the Monte Carlo sampling based path tracing and cache the indirect illumination as neural radiance, enabling a physics-faithful and easy-to-optimize inverse rendering method. |
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[2] Yongqiang Zhang, Zhipeng Hu, Haoqian Wu, Minda Zhao, Lincheng Li, Zhengxia Zou, Changjie Fan CVPR, 2023 project page We revise and provide an additional condition for the unbiased volume rendering. Following this analysis, we propose a new rendering method by scaling the SDF field with the angle between the viewing direction and the surface normal vector. |
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[1] Haoqian Wu, Tian Jian, Yongjian Fu, Bin Li, Xi Li TIP, 2020 paper We propose a condition-aware comparison scheme to measure gait pairs’ similarity via a novel module named Instructor. Also, we present a geometry-guided data augmentation approach (Dresser) to enrich dressing conditions. Furthermore, to enhance the gait representation, we propose to model temporal local information from coarse to fine. |
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Kudos to Dr. Jon Barron for sharing his website template. |