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You may wonder why "Prime", which is such a strange nickname, so here is the story: I have been having a deep voice since middle school, and that is when I earned myself the nickname "Prime" (obviously because of the famous character who's known to have a deep voice too). So no, this nickname is not something that randomly popped into my head, it is earned. ;)
I'm a CS PhD student at Stanford University,
advised by Prof. Gordon Wetzstein and Prof. Leonidas Guibas.
I am partly supported by a Stanford School of Engineering Fellowship.
Before Stanford, I was a CS master student at ETH Zürich
supervised by Prof. Luc Van Gool.
I obtained my Bachelor degree in Computer Science with first honour from King's College London in United Kingdom, where I spent some time working on information theory.
I work on long context, video generation, and (all forms of) world models, hoping they can one day forward simulate the future, and reverse engineer the past. I am also an extremely amateur body builder and car racer (with my Corvette C7 Z51 and its 6.2L V8 engine). You might spot me at one of the Equinox gyms, or in a stylish red sports car on the mountain roads behind Stanford. Email / CV / Google Scholar / Semantic Scholar / Github / Twitter / Linkedin |
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* and † indicate equal contribution |
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Shengqu Cai, Weili Nie*, Chao Liu*, Julius Berner, Lvmin Zhang, Nanye Ma, Hansheng Chen, Maneesh Agrawala, Leonidas Guibas, Gordon Wetzstein, Arash Vahdat In arXiv 2026 [Project Page][Paper] Decouple local realism and long-range coherence for fast long-video generation by combining mode-seeking teacher distillation with mean-seeking long-video supervision. |
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Shengqu Cai, Ceyuan Yang, Lvmin Zhang, Yuwei Guo, Junfei Xiao, Ziyan Yang, Yinghao Xu, Zhenheng Yang, Alan Yuille, Leonidas Guibas, Maneesh Agrawala, Lu Jiang, Gordon Wetzstein In ICLR 2026 [Project Page][Paper] Learnable sparse attention routing enables minute-long context with short-video cost, pruning most token pairs while preserving minute-long context coherence. |
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Lvmin Zhang, Shengqu Cai, Muyang Li, Gordon Wetzstein, Maneesh Agrawala In NeurIPS 2025 (Spotlight) [Project Page] [Paper] [Code] Frame context packing for next-frame prediction enables longer contexts within fixed sequence budgets, with drift prevention to reduce error accumulation. |
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Yiming Wang, Qihang Zhang*, Shengqu Cai*, Tong Wu†, Jan Ackermann†, Zhengfei Kuang†, Yang Zheng†, Frano Rajič†, Siyu Tang, Gordon Wetzstein In CVPR 2026 [Project Page][Paper] Purely implicit time- and camera-controlled 4D video diffusion that enables decoupled control over world time and camera pose (bullet-time effects). |
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Linxi Xie*, Lisong C. Sun*, Ashley Neall, Tong Wu, Shengqu Cai, Gordon Wetzstein In CVPR Findings 2026 [Project Page] [Paper] Interactive human-centric video world simulation conditioned on tracked head pose and joint-level hand poses. |
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Shengqu Cai, Eric Ryan Chan, Yunzhi Zhang, Leonidas Guibas, Jiajun Wu, Gordon Wetzstein In CVPR 2025 [Project Page][Paper][Code][Demo] Training-free customized image generation model that scales to any instance and any context. |
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Junfei Xiao, Ceyuan Yang, Lvmin Zhang, Shengqu Cai, Yang Zhao, Yuwei Guo, Gordon Wetzstein, Maneesh Agrawala, Alan Yuille, Lu Jiang In ICLR 2026 [Project Page] [Paper] Top-down keyframe planning with bottom-up long-context video synthesis, using interleaved training to adapt MM-DiT for stable and efficient multi-scene generation. |
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Jan Ackermann, Jonas Kulhanek, Shengqu Cai, Haofei Xu, Marc Pollefeys, Gordon Wetzstein, Leonidas Guibas, Songyou Peng In ICCV 2025 [Project Page][Paper][Code] Efficiently updates Gaussian splatting-based 3D scene reconstructions from incremental images via change detection and local optimization. |
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Di Chang*, Mingdeng Cao*, Yichun Shi, Bo Liu, Shengqu Cai, Shijie Zhou, Weilin Huang, Gordon Wetzstein, Mohammad Soleymani, Peng Wang In arXiv 2025 [Project Page] [Paper] [Code] Large-scale benchmark and baseline for instruction-guided image editing with complex non-rigid motions such as viewpoint changes, articulations, and deformations. |
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Liyuan Zhu, Shengqu Cai*, Shengyu Huang*, Gordon Wetzstein, Naji Khosravan, Iro Armeni In SIGGRAPH 2025 [Project Page][Paper][Code] Scene-level appearance transfer from a single style image to multi-view real-world scenes with semantic correspondences. |
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Di Chang, Hongyi Xu*, You Xie*, Yipeng Gao*, Zhengfei Kuang*, Shengqu Cai*, Chenxu Zhang*, Guoxian Song, Chao Wang, Yichun Shi, Zeyuan Chen, Shijie Zhou, Linjie Luo, Gordon Wetzstein, Mohammad Soleymani In CVPR 2025 (Highlight) [Project Page][Paper][Code] Human image animation using facial expressions and body movements derived from a driving video. |
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Zhengfei Kuang*, Shengqu Cai*, Hao He, Yinghao Xu, Hongsheng Li, Leonidas Guibas, Gordon Wetzstein In NeurIPS 2024 [Project Page][Paper][Code] Multi-view/multi-trajectory generation of videos sharing the same underlying content and dynamics. |
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Jihyeon Je*, Jiayi Liu*, Guandao Yang*, Boyang Deng*, Shengqu Cai, Gordon Wetzstein, Or Litany, Leonidas Guibas In SIGGRAPH Asia 2024 [Project Page][Paper] Render low fidelity animated mesh directly into animation using pre-trained 2D diffusion models, without the need of any further training/distillation. |
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Shengqu Cai, Duygu Ceylan*, Matheus Gadelha*, Chun-Hao Paul Huang, Tuanfeng Y. Wang, Gordon Wetzstein In CVPR 2024 [Project Page][Paper] Render low fidelity animated mesh directly into animation using pre-trained 2D diffusion models, without the need of any further training/distillation. |
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Shengqu Cai, Eric Ryan Chan, Songyou Peng, Mohamad Shahbazi, Anton Obukhov, Luc Van Gool, Gordon Wetzstein In ICCV 2023 [Project Page][Paper][Code] A diffusion-model based unsupervised framework capable of synthesizing novel views depicting a long camera trajectory flying into an input image. |
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Shengqu Cai, Anton Obukhov, Dengxin Dai, Luc Van Gool In CVPR 2022 [Paper][Code] 3D-free unsupervised Single view NeRF-based novel view synthesis via conditional NeRF-GAN training and inversion. |
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