Qianqian Wang

I am a postdoctoral researcher at UC Berkeley, working with Prof. Angjoo Kanazawa and Prof. Alyosha Efros. Additionally, I'm a visiting researcher at Google Research. I completed my PhD in Computer Science at Cornell Tech, Cornell University with my advisors Prof. Noah Snavely and Prof. Bharath Hariharan. Before that I received my bachelor's degree from Zhejiang University, where I worked with Prof. Xiaowei Zhou.

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Research
Shape of Motion: 4D Reconstruction from a Single Video
Qianqian Wang*, Vickie Ye*, Hang Gao*, Jake Austin, Zhengqi Li, Angjoo Kanazawa
  arXiv, 2024
project page / arXiv / code

SpatialTracker: Tracking Any 2D Pixels in 3D Space
Yuxi Xiao*, Qianqian Wang*, Shangzhan Zhang, Nan Xue, Sida Peng, Yujun Shen, Xiaowei Zhou
  CVPR, 2024 (highlight)
project page / arXiv / code

Emergent Correspondence from Image Diffusion
Luming Tang*, Menglin Jia*, Qianqian Wang*, Cheng Perng Phoo, Bharath Hariharan
NeurIPS, 2023
project page / arXiv / code

Tracking Everything Everywhere All at Once
Qianqian Wang, Yen-Yu Chang, Ruojin Cai, Zhengqi Li, Bharath Hariharan, Aleksander Holynski, Noah Snavely
ICCV, 2023 (Best Student Paper Award)
project page / arXiv / code

Doppelgangers: Learning to Disambiguate Images of Similar Structures
Ruojin Cai, Joseph Tung, Qianqian Wang, Hadar Averbuch-Elor, Bharath Hariharan, Noah Snavely
ICCV, 2023 (Oral)
project page / arXiv / code / data

DynIBaR: Neural Dynamic Image-Based Rendering
Zhengqi Li, Qianqian Wang, Forrester Cole, Richard Tucker, Noah Snavely
CVPR, 2023 (Best Paper Honorable Mention)
project page / arXiv / code

Neural Scene Chronology
Haotong Lin, Qianqian Wang, Ruojin Cai, Sida Peng, Hadar Averbuch-Elor, Xiaowei Zhou, Noah Snavely
CVPR, 2023
project page / arXiv / code

InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images
Zhengqi Li, Qianqian Wang, Noah Snavely, Angjoo Kanazawa
ECCV, 2022 (Oral)
project page / arXiv / code

Neural 3D reconstruction in the wild
Jiaming Sun, Xi Chen, Qianqian Wang, Zhengqi Li, Hadar Averbuch-Elor, Xiaowei Zhou, Noah Snavely
SIGGRAPH (Conference Proceedings), 2022
project page / arXiv / code

3D Moments from Near-Duplicate Photos
Qianqian Wang, Zhengqi Li, David Salesin, Noah Snavely, Brian Curless, Janne Kontkanen
CVPR, 2022
project page / arXiv / code

Neural 3D Scene Reconstruction with the Manhattan-world Assumption
Haoyu Guo*, Sida Peng*, Haotong Lin, Qianqian Wang, Guofeng Zhang,
Hujun Bao, Xiaowei Zhou
CVPR, 2022   (Oral)
project page / arXiv / code

Neural Rays for Occlusion-aware Image-based Rendering
Yuan Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang,
Christian Theobalt, Xiaowei Zhou, Wenping Wang
CVPR, 2022
project page / arXiv / code

Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies
Sida Peng*, Junting Dong*, Qianqian Wang, Shangzhan Zhang, Qing Shuai,
Xiaowei Zhou, Hujun Bao
ICCV, 2021
project page / code / arXiv
IBRNet: Learning Multi-View Image-Based Rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul Srinivasan, Howard Zhou,
Jon Barron, Ricardo Martin-Brualla, Noah Snavely, Thomas Funkhouser
CVPR, 2021
project page / code / arXiv
PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Material Editing and Relighting
Kai Zhang*, Fujun Luan*, Qianqian Wang, Kavita Bala, Noah Snavely
CVPR, 2021
project page / arXiv / code

Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans
Sida Peng, Yuanqing Zhang, Yinghao Xu, Qianqian Wang, Qing Shuai,
Hujun Bao, Xiaowei Zhou
CVPR, 2022   (Best Paper Candidate)
project page / arXiv / code

Learning Feature Descriptors using Camera Pose Supervision
Qianqian Wang, Xiaowei Zhou, Bharath Hariharan, Noah Snavely
ECCV, 2020   (Oral)
project page / arXiv / code

Hidden Footprints: Learning Contextual Walkability from 3d Human Trails
Jin Sun, Hadar Averbuch-Elor, Qianqian Wang, Noah Snavely
ECCV, 2020
project page / arXiv / code

Multi-Image Semantic Matching by Mining Consistent Features
Qianqian Wang, Xiaowei Zhou, Kostas Daniilidis
CVPR, 2018
arXiv / code


Thank Jon Barron for sharing his website's source code.