Zengqun Zhao

Zengqun Zhao

PhD Student, Queen Mary University of London

About

I am a final-year PhD student in Computer Science at Queen Mary University of London (QMUL), working with Prof. Ioannis Patras and supported by the Queen Mary Principal's Scholarship. I also collaborate closely with Dr. Ziquan Liu and Prof. Shaogang Gong. Previously, I earned an MSc in Control Science and Engineering from Nanjing University of Information Science & Technology (NUIST), where I worked with Prof. Qingshan Liu.

My research background spans human facial behaviour understanding, vision-language models, and generative models. My current work focuses on generative video models, particularly: (1) long-video generation, with an emphasis on preserving temporal consistency and mitigating error accumulation; (2) real-time video generation using self-rollout autoregressive diffusion models that synthesize each video segment faster than its playback duration; and (3) controllable video generation conditioned on text, audio, and action signals, including interactive world models and audio-driven avatars.

Outside of research, I am passionate about rock music, especially progressive rock, post-rock, Britpop, gothic rock, funk rock, and shoegaze. I enjoy playing guitar and singing, as well as staying active through hiking, cycling, and fitness.

Publications
Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation
Zengqun Zhao, Yanzuo Lu, Ziquan Liu, Jifei Song, Jiankang Deng, Ioannis Patras
British Machine Vision Conference (BMVC), 2026
LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion
Zengqun Zhao, Ziquan Liu, Yu Cao, Shaogang Gong, Zhensong Zhang, Jifei Song, Jiankang Deng, Ioannis Patras
European Conference on Computer Vision (ECCV), 2026
AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data
Zengqun Zhao, Ziquan Liu, Yu Cao, Shaogang Gong, Ioannis Patras
IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2025
Temporal Score Analysis for Understanding and Correcting Diffusion Artifacts
Yu Cao, Zengqun Zhao, Ioannis Patras, Shaogang Gong
IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2025
2026
Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation
Zengqun Zhao, Yanzuo Lu, Ziquan Liu, Jifei Song, Jiankang Deng, Ioannis Patras
British Machine Vision Conference (BMVC), 2026
LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion
Zengqun Zhao, Ziquan Liu, Yu Cao, Shaogang Gong, Zhensong Zhang, Jifei Song, Jiankang Deng, Ioannis Patras
European Conference on Computer Vision (ECCV), 2026
2025
AIM-Fair: Advancing Algorithmic Fairness via Selectively Fine-Tuning Biased Models with Contextual Synthetic Data
Zengqun Zhao, Ziquan Liu, Yu Cao, Shaogang Gong, Ioannis Patras
IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2025
Temporal Score Analysis for Understanding and Correcting Diffusion Artifacts
Yu Cao, Zengqun Zhao, Ioannis Patras, Shaogang Gong
IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2025
Enhancing Zero-Shot Facial Expression Recognition by LLM Knowledge Transfer
Zengqun Zhao, Yu Cao, Shaogang Gong, Ioannis Patras
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025
Oral
2023
Prompting Visual-Language Models for Dynamic Facial Expression Recognition
Zengqun Zhao, Ioannis Patras
British Machine Vision Conference (BMVC), 2023
2021
Former-DFER: Dynamic Facial Expression Recognition Transformer
Zengqun Zhao, Qingshan Liu
ACM International Conference on Multimedia (ACM MM), 2021
Learning Deep Global Multi-Scale and Local Attention Features for Facial Expression Recognition in the Wild
Zengqun Zhao, Qingshan Liu, Shanmin Wang
IEEE Transactions on Image Processing (TIP), 2021
Robust Lightweight Facial Expression Recognition Network with Label Distribution Training
Zengqun Zhao, Qingshan Liu, Feng Zhou
AAAI Conference on Artificial Intelligence (AAAI), 2021
Experiences
Research Scientist Intern
Apr 2026 – Sep 2026
Reality Labs, Meta
  • Working on video diffusion and codec avatars.
Research Intern
Apr 2025 – Mar 2026
London Research Center, Huawei R&D UK
  • Worked on video generation.
Teaching Assistant
Jan 2023 – Apr 2025
Queen Mary University of London
  • Machine Learning (Autumn 2023, 2024) — Module Lead: Prof. Ioannis Patras
  • Deep Learning and Computer Vision (Spring 2024, 2025) — Module Lead: Prof. Shaogang Gong
University College London
Jan 2024 – Mar 2024
  • Affective Computing and Human-Robot Interaction — Module Lead: Prof. Nadia Berthouze
Research Intern
Jul 2021 – Sep 2021
DAMO Academy, Alibaba Group
  • Worked on lightweight face detection and recognition.