AI researcher; PhD in deep learning and computer vision.

I am an AI researcher with a strong passion for conducting cutting-edge AI research and applying them to real-world problems. I received my PhD degree from Queen Mary University of London, London, UK, under the supervision of Prof. Shaogang (Sean) Gong. I have broad research experience spanning deep learning, 3D reconstruction, and generative AI. I have published papers in top-tier AI conferences, e.g., ICCV, CVPR, ECCV, and AAAI. See DBLP or Google Scholar for more.


E-mail: guile [DOT] wu [AT] outlook [DOT] com

Currently a Technical Team Lead and AI researcher, working on 3D reconstruction (e.g., 3D Gaussian Splatting, scene reconstruction) and generative AI (e.g., image/video generation, diffusion models).

Also have expertise in fundamental deep learning (e.g., transfer learning, lifelong learning, federated learning, knowledge distillation, unsupervised learning), autonomous driving (e.g., 3D object detection, scene simulation), and visual recognition.

• "MoVieDrive: Urban Scene Synthesis with Multi-Modal Multi-View Video Diffusion Transformer",
  G. Wu, D. Huang, D. Bai, B. Liu,
  Accepted to CVPR Findings, 2026.
• "Fast Spatial Tracking with Visual Geometry Transformer",
  C. Huang, G. Wu, D. Bai, B. Liu,
  Accepted to CVPR, 2026.
• "ArmGS: Composite gaussian appearance refinement for modeling dynamic urban environments",
  G. Wu, D. Bai, B. Liu,
  Accepted to ICRA, 2026.
• "Nighttime autonomous driving scene reconstruction with physically-based gaussian splatting",
  T. Kim, X. Chen, G. Wu, C. Huang, D. Bai, B. Liu,
  Accepted to ICRA, 2026.
• "Vqa-diff: Exploiting vqa and diffusion for zero-shot image-to-3d vehicle asset generation in autonomous driving",
  Y. Liu, Z. Yang, G. Wu, Y. Ren, K. Lin, B. Liu, Y. Liu, J. Shan,
  ECCV, 2024.
• "Towards universal LiDAR-based 3D object detection by multi-domain knowledge transfer",
  G. Wu, T. Cao, B. Liu, X. Chen, Y. Ren,
  ICCV, 2023.
• "Mv-deepsdf: Implicit modeling with multi-sweep point clouds for 3d vehicle reconstruction in autonomous driving",
  Y. Liu, K. Zhu, G. Wu, B. Liu, Y. Liu, J. Shan,
  ICCV, 2023.
• "Learning unbiased transferability for domain adaptation by uncertainty modeling",
  J. Hu, H. Zhong, F. Yang, S. Gong, G. Wu, J. Yan,
  ECCV, 2022.
• "Striking a balance between stability and plasticity for class-incremental learning",
  G. Wu, S. Gong, P. Li,
  ICCV, 2021.
• "Collaborative optimization and aggregation for decentralized domain generalization and adaptation",
  G. Wu, S. Gong,
  ICCV, 2021.
• "Peer collaborative learning for online knowledge distillation",
  G. Wu, S. Gong,
  AAAI, 2021.
• "Decentralised learning from independent multi-domain labels for person re-identification",
  G. Wu, S. Gong,
  AAAI, 2021.
• "Generalising without forgetting for lifelong person re-identification",
  G. Wu, S. Gong,
  AAAI, 2021.
• "Tracklet self-supervised learning for unsupervised person re-identification",
  G. Wu, X. Zhu, S. Gong,
  AAAI, 2020.