Hang ZOU (邹航)

Hang ZOU (邹航)

China Telecom Research Institute (CTRI)

🤗Last upadated - October 2024

I am currently focusing on standardization within Study Group 16 of the ITU-T.

Interests
  • Generative Model
Education
  • MSc in Information Technology, 2018 - 2020

    Macau University of Science and Technology

  • BEng in Automation, 2014 - 2018

    Minzu University of China

Standards

  • [Under study] ITU-T SG16, H.ILE-3DINR “Framework and requirements of 3D reconstruction systems based on implicit neural representation for immersive live experience (ILE) services”, 2024, Main Editor;
  • [Under study] ITU-T SG16, F.IGreqs “Requirements and framework of artificial intelligence-based image generation systems”, 2024, Co-Editor;
  • ITU-T SG16, F.747.15 (ex F.EVSreqs) “Requirements of event-based vision systems”, 2022, Main Editor, Approved;
  • ITU-T SG16, F.748.29 (ex F.MFDreqs) “Requirements and functions of computer audition based machinery fault diagnosis system”, 2022, Co-Editor, Approved;
  • ITU-T SG16, F.747.14 (ex F.MFSVreqs) “Requirements and capability framework of the multimodal fusion system for vision”, 2022, Co-Editor, Approved;
  • [在研] CCSA TC1,《基于视频云网融合的视联网 人工智能中台》,2024,第一起草人
  • [在研] CCSA TC1,《基于人工智能多模态技术的信息系统技术要求 第2部分:智能交互系统》,2024-0036T-YD,第一起草人
  • [在研] CCSA TC1,《基于人工智能多模态技术的信息系统技术要求 第1部分:生物特征识别系统》,2023-1069T-YD,第一起草人

Patents

  • 三维图像的合成重建方法及相关设备,2023,第一发明人,CN117830374A
  • 图像生成器的训练方法、图像重建方法、装置和存储介质,2023,第一发明人,CN117709428A
  • 图像处理方法及装置、存储介质及电子设备,2023,第一发明人,CN116993590A
  • 图像分类方法、装置、电子设备和计算机可读存储介质,2023,第一发明人,CN116977742A
  • 图像处理方法、装置、计算机可读存储介质及电子设备,2023,第四发明人,CN116630514A
  • 人体图像三维重建方法、装置、设备及存储介质,2023,第一发明人,CN116563467A
  • 三维模型生成方法及装置、存储介质及电子设备,2023,第三发明人,CN116597087A
  • 图像处理方法及装置、存储介质及电子设备,2023,第四发明人,CN116597173A
  • [已授权] 模型的训练方法、训练装置、电子设备和可读存储介质,2022,第一发明人,CN115439610B
  • [已授权] 异常数据识别模型的训练方法及相关设备,2022,第一发明人,CN115238805B
  • 图像生成方法及装置、存储介质和电子设备,2022,第三发明人,CN115272576A
  • [已授权] 图像生成方法及装置、存储介质和电子设备,2022,第三发明人,CN115100360B
  • [已授权] 图像生成方法及装置、存储介质和电子设备,2022,第三发明人,CN115272575B
  • [已授权] 图像重建方法及装置、计算机存储介质、电子设备,2022,第一发明人,CN115205117B
  • 基于二维图像的三维重建方法、系统、设备及存储介质,2022,第一发明人,CN115018994A
  • [已授权] 图像生成方法、装置、电子设备及计算机可读存储介质,2022,第三发明人,CN115063536B
  • 三维物体的图像渲染方法、装置及电子设备,2022,第三发明人,CN114863007A
  • 图像处理方法、装置、存储介质及电子设备,2021,第二发明人,CN114332334A
  • [已授权] 通用三维模型重建方法及装置、存储介质及电子设备,2021,第三发明人,CN114299252B
  • [已授权] 人脸图像生成方法及装置、人脸识别方法、设备、介质,2021,第一发明人,CN114255502B

Papers

  • [1] H. Zou et al., “A Unified Framework for Iris Anti-Spoofing: Introducing IrisGeneral Dataset and Masked-MoE Method,” arXiv preprint arXiv:2408.09752, 2024.
  • [2] Q. Zhang, Q. Liu, and H. Zou, “CDNeRF: A multi-modal feature guided neural radiance fields,” presented at the CAAI International Conference on Artificial Intelligence, Springer, 2022, pp. 204–215.
  • [3] H. Zhang, M. Zhang, Z. He, H. Zou, and R. Wang, “Coarse-to-Fine Iris Recognition Based on Multi-variant Ordinal Measures Feature Complementarity,” presented at the Biometric Recognition: 12th Chinese Conference, CCBR 2017, Shenzhen, China, October 28-29, 2017, Proceedings 12, Springer, 2017, pp. 411–419.
  • [4] X. Hu et al., “Fine-Grained Prompt Learning for Face Anti-Spoofing,” presented at the ACM Multimedia 2024,
  • [5] H. Zou, H. Zhang, X. Li, J. Liu, and Z. He, “Generation textured contact lenses iris images based on 4DCycle-GAN,” presented at the 2018 24th International Conference on Pattern Recognition (ICPR), IEEE, 2018, pp. 3561–3566.
  • [6] H. Zou et al., “La-SoftMoE CLIP for Unified Physical-Digital Face Attack Detection,” arXiv preprint arXiv:2408.12793, 2024.
  • [7] Q. Zhang, B. H. Wang, M. C. Yang, and H. Zou, “MMNeRF: Multi-Modal and Multi-View Optimized Cross-Scene Neural Radiance Fields,” IEEE Access, vol. 11, pp. 27401–27413, 2023.
  • [8] H. Zou et al., “Multi-angle Consistent Generative NeRF with Additive Angular Margin Momentum Contrastive Learning,” presented at the Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 930–939.
  • [9] J. Guo et al., “Style-conditional Prompt Token Learning for Generalizable Face Anti-spoofing,” presented at the ACM Multimedia 2024,