Classifying vehicles with convolutional neural network and feature encoding. - Shuang Wang 005; Zhengqi Li; Haijun Zhang 002; Yuzhu Ji; Yan Li 040 (INDIN, 2016)

Large Scale Image Mosaic Construction for Agricultural Applications. - Zhengqi Li; Volkan Isler (IEEE Robotics Autom. Lett., 2016)

MegaDepth: Learning Single-View Depth Prediction From Internet Photos. - Zhengqi Li; Noah Snavely (CVPR, 2018)

Learning Intrinsic Image Decomposition From Watching the World. - Zhengqi Li; Noah Snavely (CVPR, 2018)

CGIntrinsics: Better Intrinsic Image Decomposition Through Physically-Based Rendering. - Zhengqi Li; Noah Snavely (ECCV (3), 2018)

Learning the Depths of Moving People by Watching Frozen People. - Zhengqi Li; Tali Dekel; Forrester Cole; Richard Tucker 001; Noah Snavely; Ce Liu 001; William T. Freeman (CVPR, 2019)

UprightNet: Geometry-Aware Camera Orientation Estimation From Single Images. - Wenqi Xian; Zhengqi Li; Noah Snavely; Matthew Fisher; Jonathan Eisenmann; Eli Shechtman (ICCV, 2019)

Crowdsampling the Plenoptic Function. - Zhengqi Li; Wenqi Xian; Abe Davis; Noah Snavely (ECCV (1), 2020)

Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes. - Zhengqi Li; Simon Niklaus; Noah Snavely; Oliver Wang (CVPR, 2021)

MannequinChallenge: Learning the Depths of Moving People by Watching Frozen People. - Zhengqi Li; Tali Dekel; Forrester Cole; Richard Tucker 001; Noah Snavely; Ce Liu 001; William T. Freeman (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Learning Geometry, Appearance and Motion in the Wild. - Zhengqi Li (2021)

3D Moments from Near-Duplicate Photos. - Qianqian Wang 002; Zhengqi Li; David Salesin; Noah Snavely; Brian Curless; Janne Kontkanen (CVPR, 2022)

Deformable Sprites for Unsupervised Video Decomposition. - Vickie Ye; Zhengqi Li; Richard Tucker 001; Angjoo Kanazawa; Noah Snavely (CVPR, 2022)

IRON: Inverse Rendering by Optimizing Neural SDFs and Materials from Photometric Images. - Kai Zhang 045; Fujun Luan; Zhengqi Li; Noah Snavely (CVPR, 2022)

InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images. - Zhengqi Li; Qianqian Wang 002; Noah Snavely; Angjoo Kanazawa (ECCV (1), 2022)

Structure and Motion from Casual Videos. - Zhoutong Zhang; Forrester Cole; Zhengqi Li; Michael Rubinstein; Noah Snavely; William T. Freeman (ECCV (33), 2022)

Neural 3D Reconstruction in the Wild. - Jiaming Sun; Xi Chen 079; Qianqian Wang 002; Zhengqi Li; Hadar Averbuch-Elor; Xiaowei Zhou 001; Noah Snavely (SIGGRAPH (Conference Paper Track), 2022)

Persistent Nature: A Generative Model of Unbounded 3D Worlds. - Lucy Chai; Richard Tucker 001; Zhengqi Li; Phillip Isola; Noah Snavely (CVPR, 2023)

DynIBaR: Neural Dynamic Image-Based Rendering. - Zhengqi Li; Qianqian Wang 002; Forrester Cole; Richard Tucker 001; Noah Snavely (CVPR, 2023)

Omnimatte3D: Associating Objects and Their Effects in Unconstrained Monocular Video. - Mohammed Suhail; Erika Lu; Zhengqi Li; Noah Snavely; Leonid Sigal; Forrester Cole (CVPR, 2023)

Tracking Everything Everywhere All at Once. - Qianqian Wang 002; Yen-Yu Chang; Ruojin Cai; Zhengqi Li; Bharath Hariharan; Aleksander Holynski; Noah Snavely (ICCV, 2023)

Generative Image Dynamics. - Zhengqi Li; Richard Tucker 001; Noah Snavely; Aleksander Holynski (CVPR, 2024)

Streetscapes: Large-scale Consistent Street View Generation Using Autoregressive Video Diffusion. - Boyang Deng; Richard Tucker 001; Zhengqi Li; Leonidas J. Guibas; Noah Snavely; Gordon Wetzstein (SIGGRAPH (Conference Paper Track), 2024)

Shape of Motion: 4D Reconstruction from a Single Video. - Qianqian Wang; Vickie Ye; Hang Gao; Jake Austin; Zhengqi Li; Angjoo Kanazawa (CoRR, 2024)

Can Generative Video Models Help Pose Estimation? - Ruojin Cai; Jason Y. Zhang 004; Philipp Henzler; Zhengqi Li; Noah Snavely; Ricardo Martin-Brualla (CVPR, 2025)

Stereo4D: Learning How Things Move in 3D from Internet Stereo Videos. - Linyi Jin; Richard Tucker 001; Zhengqi Li; David Fouhey; Noah Snavely; Aleksander Holynski (CVPR, 2025)

MegaSaM: Accurate, Fast and Robust Structure and Motion from Casual Dynamic Videos. - Zhengqi Li; Richard Tucker 001; Forrester Cole; Qianqian Wang 002; Linyi Jin; Vickie Ye; Angjoo Kanazawa; Aleksander Holynski; Noah Snavely (CVPR, 2025)

Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion. - Xun Huang; Zhengqi Li; Guande He; Mingyuan Zhou; Eli Shechtman (CoRR, 2025)