I am a fourth-year PhD student at the IIAU-Lab in Dalian University of Technology, under the supervision of Prof. Huchuan Lu (IEEE Fellow) and Prof. Xu Jia. I am selected into the China Association for Science and Technology (CAST) Young Talent Support Program - Doctoral Student Initiative. I obtained my Master's degree from Tianjin University supervised by Prof. Pengfei Zhu and Prof. Bing Cao. I obtained my Bachelor's degree from Dalian Maritime University. My research focuses on Video World Models.
Alibaba
2026.5~Now Research Intern in HappyOyster Team, Alibaba Group (Beijing)
Advisor: Wenbo Su
Topic: Real-Time Interactive Streaming Video Generation
Kuaishou
2024.7~2026.5 Research Intern in Kling Team, Kuaishou Technology (Shenzhen)
Advisors: Xiaoyu Shi, Xintao Wang
Topic: Video Generation
ByteDance
2022.4~2022.12 Research Intern in ByteDance Intelligent Creation Lab (Beijing)
Advisors: Lijie Liu, Qian He
Topic: Image Generation
Selected Publications
[CVPR 2026 CCF A] MultiShotMaster: A Controllable Multi-Shot Video Generation Framework
Qinghe Wang, Xiaoyu Shi✉, Baolu Li, Weikang Bian, Quande Liu, Huchuan Lu, Xintao Wang, Pengfei Wan, Kun Gai, Xu Jia✉ [Paper] [Project Page] [Code] [🥇 1st Place at AAAI CVM 2026]
The first controllable multi-shot video generation framework that supports text-driven inter-shot consistency, customized subject with motion control, and background-driven customized scene. Both shot counts and shot durations are variable.
A unified reference-based VFX video generation framework allows users to reproduce diverse dynamic effects from reference videos onto target content.
[CVPR 2026 CCF A] Group Editing: Edit Multiple Images in One Go
Yue Ma, Xinyu Wang, Qianli Ma, Qinghe Wang✉(co-corresponding), Mingzhe Zheng, Xiangpeng Yang, Hao Li, Chongbo Zhao, Jixuan Ying, Harry Yang, Hongyu Liu✉, Qifeng Chen [Paper] [Project Page] [Code]
A unified group-image editing framework enables users to apply consistent and diverse editing across multiple related images by leveraging explicit geometric correspondences and implicit video priors.
A unified framework takes a reference video containing the desired semantics as input and employs a HyperNetwork to generate lightweight, semantic-specific LoRA modules for semantic-controllable video generation.
[SIGGRAPH 2026 CCF A] EasyVFX: Frequency-Driven Decoupling for Resource-Efficient VFX Generation Yue Ma, Xu Ye, Qinghe Wang✉(co-corresponding), Yucheng Wang, Hongyu Liu, Yinhan Zhang, Xinyu Wang, Yuanpeng Che, Shanhui Mo, Paul Liang, Fangneng Zhan✉, Qifeng Chen [Paper] [Project Page] [Code]
A VFX video generation framework takes a reference VFX video as input and employs a frequency-aware decoupling mechanism to enable resource-efficient, high-fidelity visual effect transfer for controllable video generation.
[SIGGRAPH 2025 CCF A] CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generation
Qinghe Wang*, Yawen Luo*(co-first), Xiaoyu Shi✉, Xu Jia✉, Huchuan Lu, Tianfan Xue✉, Xintao Wang, Pengfei Wan, Di Zhang, Kun Gai. [Paper] [Project Page]
A 3D-aware and controllable text-to-video generation method allows users to manipulate objects and camera jointly in 3D space for high-quality cinematic video creation.
