高伟，博士，必威betway西汉姆联助理教授/研究员/博士生导师，IEEE/CCF/CSIG Senior Member，国际IEEE电路与系统学会视觉信号处理和通信技术委员会委员（IEEE CASS VSPC-TC）、亚太信号与信息处理协会图像、视频与多媒体技术委员会委员（APSIPA IVM-TC），广东省青年拔尖人才、深圳市高层次孔雀计划人才。具有在香港、新加坡和美国学习与工作经历，曾在工业界从事研发工作。长期从事视觉感知驱动的多媒体编码与处理、深度学习与人工智能领域的研究，特别是沉浸式与3D视觉媒体信息处理技术（包括点云、光场、全景、多视点/双目3D、NeRF/3D Gaussian Splatting、网格等）。研究方向主要包括：（1）多媒体编码：面向人机感知共友好的多媒体编码（三维点云、图像视频）、深度学习智能编码、多媒体通信与传输；（2）多媒体处理：点云处理与分析、图像/视频处理与分析、沉浸式与3D视觉媒体处理与分析（质量评价与显著性分割、增强复原与机器分析、多模态融合）；（3）深度学习与人工智能：多模态大模型/AIGC生成式人工智能/具身智能/可信人工智能技术、深度网络轻量化与软硬件实现、开源项目。

主要科研成果发表在相关领域高水平国际期刊（如IEEE TPAMI、TIP、TCSVT、TMM、TNNLS、TCYB、TGRS和IJCV等）和高水平国际会议（如CVPR、ECCV、AAAI、ACM MM、DCC等）上120余篇，申请或授权美国/中国/PCT专利90余项（授权28项），积极参与多媒体与人工智能技术的标准制定工作并提交技术提案40余项（采纳20项）。多篇论文入选ESI高被引论文和优秀论文奖（2篇论文入选ESI高被引，6篇论文获得优秀论文奖）。由于在3D沉浸式媒体方面的研究荣获2021年IEEE多媒体学术新星奖项，荣获2022年CCF优秀图形开源软件奖项、2023年和2022年深圳市科学技术协会优秀科技学术论文奖（4项）、2021年CCF-腾讯犀牛鸟优秀专利奖、2020年和2019年连续两年CCF-腾讯犀牛鸟基金、2019年广东省计算机学会优秀论文一等奖（第1作者论文）。

曾经或现在正在担任多个多媒体计算与机器学习领域国际重要SCI期刊副编辑（Associate Editor），包括Signal Processing（Elsevier）、Neural Processing Letters（Springer）等。担任中国计算机学会多媒体技术专委会执行委员（CCF TCMM）、中国图象图形学学会多媒体专业委员会委员（CSIG TCMM）和三维视觉专业委员会委员（CSIG TC3DV）。担任ZTE Communications上点云处理与应用专题（Special Issue）的客座编委（Guest Editor）。在IEEE ICME 2023、ACM MM 2022、IEEE VCIP 2022和IEEE ICME 2021会议上组织过交互式媒体质量评价、点云编码与处理等领域的研讨会（Workshop）和专题会议（Special Session）。担任IEEE IJCNN 2024、IEEE ICIP 2024、IEEE ICME 2023点云相关主题的讲习班（Tutorial）讲者。国家自然科学基金、广东省与深圳市项目评审专家。担任多个国际顶级期刊IEEE TIP、TVCG、TCSVT、TMM、TNNLS、TCYB等以及国际重要学术会议CVPR、ECCV、AAAI、ACM MM、IJCAI等的审稿人，多个国际学术会议程序委员会委员与组织方等。

课题组搭建和维护多个重要开源项目，包括OpenPointCloud（点云编码与处理开源库）、OpenHardwareVC（AVS3 8K硬件编码器开源库）、OpenAICoding（多平台支持的深度学习图像视频编码开源库）、OpenCompression（视觉媒体压缩开源库）、OpenVision（计算机视觉开源库）、OpenDatasets（多媒体计算与人工智能领域的大规模特色数据集系列开源库）等。

正在带领课题组积极从事沉浸式与3D视觉媒体处理技术研究。课题组致力于提升沉浸式与3D视觉媒体的观看体验与工业应用，促进新兴与未来多媒体与视觉信息处理技术发展（重要应用领域包括三维视觉技术支持的可靠无人系统/自动驾驶/自主导航、沉浸式媒体感知技术支持的虚拟现实/增强现实等）。所指导的研究生获得国家奖学金、北京市优秀毕业生、必威betway西汉姆联优秀毕业生、必威betway西汉姆联三好学生标兵等荣誉。

欢迎优秀的本科生和硕士生保送和报考必威betway西汉姆联的硕士和博士研究生，同时欢迎申请课题组的博士后和访问职位（包括“博雅”博士后项目：基本年薪50万/年起，两年资助期，优异者出站后可转为特聘副研究员），从事多媒体计算与人工智能相关热门与前沿课题的研究探索。请查看主页：https://gaowei262.github.io/（查看最新招生与科研信息）。

作为负责人曾经或正在负责10余项国家级与省市级重要科研项目，包括科技部国家重点研发计划项目/课题（2项）、国家自然科学基金项目/课题（重点项目课题1项，面上项目1项，青年项目1项）、广东省自然科学基金项目（面上项目2项）、深圳市基础研究项目（重点项目1项，面上项目2项）等。作为研究骨干参与国家自然科学基金项目（3项）、香港研究资助局优配研究基金项目（1项）、香港创新科技署项目（1项）等。课题组与工业界有广泛的技术研发合作，承担多项企业委托项目（腾讯、华为、联想等），推动相关技术应用和落地。

n Senior Member of IEEE

n Senior Member of China CCF/CSIG

n 国际IEEE电路与系统学会视觉信号处理和通信技术委员会委员（IEEE CASS VSPC-TC）

n 亚太信号与信息处理协会图像、视频与多媒体技术委员会委员（APSIPA IVM-TC）

n 中国计算机学会多媒体技术专委会执行委员、中国图象图形学学会多媒体专业委员会委员、中国图象图形学学会三维视觉专业委员会委员

n 国际SCI期刊Signal Processing副编辑

n 国际SCI期刊Neural Processing Letters副编辑

n 国际SCI期刊IET Image Processing副编辑

n 国际SCI期刊IET Electronics Letters副编辑

n 国际ZTE Communications期刊专刊客座编辑（Special Issue on 3D Point Cloud Processing and Applications）

n Tutorial Speaker, Tutorial on Neural Network Design and Optimization for 3D Point Cloud Computing (NNPC) at IEEE IJCNN 2024

n Tutorial Speaker, Tutorial on Point Cloud Coding, Enhancement and Analysis: Towards Perception and Reliability (PCEA) at IEEE ICIP 2024

n Tutorial Speaker, Tutorial on 3D Point Cloud Compression and Processing for Multi-dimensional Applied Perception (PCP-MAP) at IEEE ICME 2023

n Organizer, International Workshop on Perception-inspired Communication and Processing for Immersive and Interactive Multimedia (PCPI2M) at IEEE ICME 2023

n Organizer, Special Session on 3D Point Cloud Acquisition, Processing and Communication (3DPC-APC) at IEEE VCIP 2022

n Organizer, International Workshop on Advances in Point Cloud Compression, Processing and Analysis (APCCPA) at ACM MM 2022

n Organizer, International Workshop on Quality of Experience in Interactive Multimedia (QoEIM) at IEEE ICME 2021

1. Jilong Wang, Wei Gao, Ge Li, “Zoom to Perceive Better: No-reference Point Cloud Quality Assessment via Exploring Effective Multiscale Feature,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2024.

2. Ruonan Zhang, Ge Li, Wei Gao, Thomas H. Li, “ComPoint: Can Complex-valued Representation Benefit Point Cloud Place Recognition?,” IEEE Transactions on Intelligent Transportation Systems (TITS), 2024.

3. Zhiyi Pan, Nan Zhang, Wei Gao, Shan Liu, Ge Li, “Less is More: Label Recommendation for Weakly Supervised Point Cloud Semantic Segmentation,” 2024 AAAI Conference on Artificial Intelligence (AAAI), 2024.

4. Wang Liu, Wei Gao, Xingming Mu, “Fast Inter-Frame Motion Prediction for Compressed Dynamic Point Cloud Attribute Enhancement,” 2024 AAAI Conference on Artificial Intelligence (AAAI), 2024.

5. Huiming Zhang, Wei Gao, “End-to-End RGB-D Image Compression via Exploiting Channel-Modality Redundancy,” 2024 AAAI Conference on Artificial Intelligence (AAAI), 2024.

6. Yang Guo, Wei Gao, Ge Li, “Interpretable Task-inspired Adaptive Filter Pruning For Neural Networks Under Multiple Constraints,” International Journal of Computer Vision (IJCV), 2024.

7. Wei Gao, Hang Yuan, Ge Li, Zhu Li, Hui Yuan, “Low Complexity Coding Unit Decision in Video-Based Point Cloud Compression,” IEEE Transactions on Image Processing (TIP), 2024.

8. Hang Yuan, Wei Gao, Siwei Ma, Yiqiang Yan, “Divide-and-Conquer-Based RDO-Free CU Partitioning for 8K Video Compression,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 2024.

9. Yiting Shao, Ge Li, Qi Zhang, Wei Gao, Shan Liu, “Nonrigid Registration-Based Progressive Motion Compensation for Point Cloud Geometry Compression,” IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023.

10. Jilong Wang, Wei Gao, Ge Li, “Applying Collaborative Adversarial Learning to Blind Point Cloud Quality Measurement,” IEEE Transactions on Instrumentation and Measurement (TIM), vol. 72, pp. 1-15, 2023.

11. Zetao Yang, Wei Gao, Ge Li, Yiqiang Yan, “SUR-Driven Video Coding Rate Control for Jointly Optimizing Perceptual Quality and Buffer Control,” IEEE Transactions on Image Processing (TIP), accepted in August 2023.

12. Wei Gao, Shangkun Sun, Huiming Zheng, Yuyang Wu, Hua Ye, Yongchi Zhang, “OpenDMC: An Open-Source Library and Performance Evaluation for Deep-learning-based Multi-frame Compression,” ACM International Conference on Multimedia (ACM MM), 2023.

13. Songlin Fan, Wei Gao, “Screen-based 3D Subjective Experiment Software,” ACM International Conference on Multimedia (ACM MM), 2023.

14. Hang Yuan, Wei Gao, “OpenFastVC: An Open Source Library for Video Coding Fast Algorithm Implementation,” ACM International Conference on Multimedia (ACM MM), 2023.

15. Xianghao Zang, Wei Gao, Ge Li, Han Fang, Chao Ban, Zhongjiang He, Hao Sun, “A Baseline Investigation: Transformer-based Cross-view Baseline for Text-based Person Search,” ACM International Conference on Multimedia (ACM MM), 2023.

16. Junhong Lin, Shufan Pei, Bing Chen, Nanfeng Jiang, Wei Gao, Tiesong Zhao, “LDRM: Degradation Rectify Model for Low-light Imaging via Color-Monochrome Cameras,” ACM International Conference on Multimedia (ACM MM), 2023.

17. Lvfang Tao, Wei Gao, Ge Li, Chenhao Zhang, “AdaNIC: Towards Practical Neural Image Compression via Dynamic Transform Routing,” International Conference on Computer Vision (ICCV), 2023.

18. Jin Chen, Aiping Huang, Wei Gao, Yuzhen Niu, Tiesong Zhao, “Joint Shared-and-Specific Information for Deep Multi-View Clustering,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023.

19. Yuanqi Chen, Shangkun Sun, Ge Li, Wei Gao, Thomas H. Li, “Closing the Gap between Theory and Practice during Alternating Optimization for GANs,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.

20. Wei Gao, Hang Yuan, Guibiao Liao, Zixuan Guo, Jianing Chen, “PP8K: A New Dataset for 8K UHD Video Compression and Processing,” IEEE MultiMedia (IEEE MM), 2023.

21. Nan Zhang, Zhiyi Pan, Thomas H. Li, Wei Gao, Ge Li, “Improving Graph Representation for Point Cloud Segmentation via Attentive Filtering,” IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, BC, Canada, 2023, pp. 1244-1254.

22. Wei Gao, Songlin Fan, Ge Li, Weisi Lin, “A Thorough Benchmark and A New Model for Light Field Saliency Detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 45, no. 7, pp. 8003-8019, 1 July 2023.

23. Fei Song, Ge Li, Xiaodong Yang, Wei Gao, Shan Liu, “Block-Adaptive Point Cloud Attribute Coding With Region-Aware Optimized Transform,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 33, no. 8, pp. 4294-4308, Aug. 2023.

24. Yuanqi Chen, Cece Jin, Ge Li, Thomas H. Li, Wei Gao, “Mitigating Label Noise in GANs via Enhanced Spectral Normalization,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2023.

25. Hao Liu, Hui Yuan, Junhui Hou, Raouf Hamzaoui, Wei Gao, “PUFA-GAN: A Frequency-Aware Generative Adversarial Network for 3D Point Cloud Upsampling,” IEEE Transactions on Image Processing (TIP), 2022.

26. Ruonan Zhang, Wei Gao, Ge Li, Thomas Li, “QINet: Decision Surface Learning and Adversarial Enhancement for Quasi-Immune Completion of Diverse Corrupted Point Clouds,” IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 60, pp. 1-14, 2022.

27. Guanghui Yue, Siying Li, Tianwei Zhou, Miaohui Wang, Jingfeng Du, Tianfu Wang, Qiuping Jiang, Wei Gao, “Adaptive Context Exploration Network for Polyp Segmentation in Colonoscopy Images,” IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 2022.

28. Runmin Cong, Haowei Yang, Qiuping Jiang, Wei Gao, Haisheng Li, Yao Zhao, and Sam Kwong, “BCS-Net: Boundary, Context and Semantic for Automatic COVID-19 Lung Infection Segmentation from CT Images,” IEEE Transactions on Instrumentation and Measurement (TIM), 2022.

29. Songlin Fan, Wei Gao, Ge Li, “Salient Object Detection for Point Clouds,” European Conference on Computer Vision (ECCV), 2022.

30. Wei Gao, Hua Ye, Ge Li, Huiming Zheng, Yuyang Wu, Liang Xie, “OpenPointCloud: An Open-Source Algorithm Library of Deep Learning Based Point Cloud Compression,” ACM International Conference on Multimedia (ACM MM), 2022.

31. Hang Yuan, Wei Gao, Ge Li, Zhu Li, “Rate-Distortion-Guided Learning Approach with Cross-Projection Information for V-PCC Fast CU Decision,” ACM International Conference on Multimedia (ACM MM), 2022.

32. Wei Gao, Hang Yuan, Yang Guo, Lvfang Tao, Zhanyuan Cai, Ge Li, “OpenHardwareVC: An Open Source Library for 8K UHD Video Coding Hardware Implementation,” ACM International Conference on Multimedia (ACM MM), 2022.

33. Guibiao Liao, Wei Gao, Ge Li, Junle Wang, Sam Kwong, “Cross-Collaborative Fusion-Encoder Network for Robust RGB-Thermal Salient Object Detection,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2022.

34. Wei Gao, Yang Guo, Siwei Ma, Ge Li, and Sam Kwong, “Efficient Neural Network Compression Inspired by Compressive Sensing,” IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.

35. Dinghao Yang, Wei Gao, Hui Yuan, Junhui Hou, Ge Li, Sam Kwong, “Exploiting Manifold Feature Representation for Efficient Classification of 3D Point Clouds,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 19, no. 1, pp 1-21, 2023.

36. Ruonan Zhang, Jingyi Chen, Wei Gao, Ge Li, Thomas Li, “PointOT: Interpretable Geometry-Inspired Point Cloud Generative Model via Optimal Transport,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 32, no. 10, pp. 6792-6806, Oct. 2022.

37. Xiaoyu Zhang, Wei Gao, Ge Li, Qiuping Jiang, Runmin Cong, “Image Quality Assessment Driven Reinforcement Learning for Mixed Distorted Image Restoration,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 19, no. 1, February 2023.

38. Zhuangzi Li, Ge Li, Thomas Li, Shan Liu, Wei Gao, “Semantic Point Cloud Upsampling,” IEEE Transactions on Multimedia (TMM), vol. 25, pp. 3432-3442, 2023.

39. Xianghao Zang, Ge Li, Wei Gao, “Multidirection and Multiscale Pyramid in Transformer for Video-Based Pedestrian Retrieval,” IEEE Transactions on Industrial Informatics (TII), 2022.

40. Yang Guo, Wei Gao, Siwei Ma, Ge Li, “Accelerating Transform Algorithm Implementation for Efficient Intra Encoder of 8K UHD Videos,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 18, no. 4, pp. 1-20, 2022.

41. Wei Gao, Guibiao Liao, Siwei Ma, Ge Li, Yongsheng Liang, and Weisi Lin, “Unified Information Fusion Network for Multi-Modal RGB-D and RGB-T Salient Object Detection,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 32, no. 4, pp. 2091-2106, April 2022.

42. Wei Gao, Qiuping Jiang, Ronggang Wang, Siwei Ma, Ge Li, and Sam Kwong, “Consistent Quality Oriented Rate Control in HEVC via Balancing Intra and Inter Frame Coding,” IEEE Transactions on Industrial Informatics (TII), vol. 18, no. 3, pp. 1594-1604, March 2022.

43. Chunyang Fu, Ge Li, Rui Song, Wei Gao, Shan Liu, “OctAttention: Octree-based Large-scale Contexts Model for Point Cloud Compression,” AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, February 22 to March 1, 2022.

44. Wenbo Zhao, Xianming Liu, Zhiwei Zhong, Junjun Jiang, Wei Gao, Ge Li, Xiangyang Ji, “Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation,” IEEE/CVF International Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, Louisiana, June 21-24, 2022.

45. Zhenyu Peng, Qiuping Jiang, Feng Shao, Wei Gao, Weisi Lin, “LGGD+: Image Retargeting Quality Assessment by Measuring Local and Global Geometric Distortions,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), September 2021.

46. Fei Song, Yiting Shao, Wei Gao, Haiqiang Wang, and Thomas Li, “Layer-Wise Geometry Aggregation Framework for Lossless LiDAR Point Cloud Compression,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), vol. 31, no. 12, pp. 4603-4616, Dec. 2021.

47. Yudong Mao, Qiuping Jiang, Runmin Cong, Wei Gao, Feng Shao, Sam Kwong, “Cross-modality Fusion and Progressive Integration Network for Saliency Prediction on Stereoscopic 3D Images,” IEEE Transactions on Multimedia (TMM), 2021.

48. Wei Gao, Linjie Zhou, and Lvfang Tao, “A Fast View Synthesis Implementation Method for Light Field Applications,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), vol. 17, no. 4, pp. 1-20, 2021.

49. Zhuangzi Li, Ge Li, Thomas Li, Shan Liu, Wei Gao, “Information-Growth Attention Network for Image Super-Resolution,” ACM International Conference on Multimedia (ACM MM), Chengdu, China, 20-24 October, 2021.

50. Liang Xie, Wei Gao, Huiming Zheng, Hua Ye, “Semantic-Aware Visual Decomposition for Point Cloud Geometry Compression,” 2024 Data Compression Conference (DCC), Snowbird, Utah, March 19-22, 2024.

51. Liang Xie, Wei Gao, Songlin Fan, Zhaojian Yao, “PDNet: Parallel Dual-branch Network for Point Cloud Geometry Compression and Analysis,” 2024 Data Compression Conference (DCC), Snowbird, Utah, March 19-22, 2024.

52. Zhiyang Qi, Wei Gao, “Variable-Rate Point Cloud Geometry Compression Based on Feature Adjustment and Interpolation,” 2024 Data Compression Conference (DCC), Snowbird, Utah, March 19-22, 2024.

53. Zhuozhen Yu, Wei Gao, “When Dynamic Neural Network Meets Point Cloud Compression: Computation-Aware Variable Rate and Checkerboard Context,” 2024 Data Compression Conference (DCC), Snowbird, Utah, March 19-22, 2024.

54. Yuyang Wu, Wei Gao, “End-to-end Lossless Compression of High Precision Depth Maps Guided by Pseudo-residual,” Data Compression Conference (DCC), Snowbird, Utah, USA, pp. 489-489, March 22-24, 2022.

55. Liang Xie, Wei Gao, Huiming Zheng, Ge Li, “SPCGC: Scalable Point Cloud Geometry Compression for Machine Vision,” 2024 IEEE International Conference on Robotics and Automation (ICRA), May 13-17, 2024, Yokohama, Japan.

1. Systems and Methods for Rate Control in Video Coding using Joint Machine Learning and Game Theory, United States Patent, US10542262B2, Jan. 21, 2020.

2. Method for Initial Quantization Parameter Optimization in Video Coding, United States Patent, US10560696B2, Feb. 11, 2020.

3. Methods, Apparatus, and Computer Readable Storage Mediums for Determination of Neural Network Pruning, United States Patent, Filed in Dec. 9, 2021.

4. Methods, Apparatus, Devices, Mediums and Products for Object Detection Network Design, United States Patent, Filed in May 14, 2021.

5. 基于可变码率的点云压缩方法、装置、设备及存储介质，PCT国际专利申请，PCT/CN2024/073221，2024年1月19日。

6. 码率可变的点云压缩方法、装置、设备及存储介质，PCT国际专利申请，PCT/CN2024/073219，2024年1月19日。

7. 点云语义信息的获取方法、获取装置、设备及介质，PCT国际专利申请，PCT/CN2023/118040，2023年9月11日。

8. 一种面向学习模型的编码决策处理方法、装置及设备，PCT国际专利申请，PCT/CN2022/139790，2022年10月14日。

9. 一种图像压缩方法、装置、电子设备及存储介质，PCT国际专利申请，PCT/CN2022/133355，2022年7月28日。

10. 剪枝模块的确定方法、装置及计算机可读存储介质，PCT国际专利申请，PCT/CN2021/136849，2021年12月9日。

11. 目标检测网络构建优化方法、装置、设备、介质及产品，PCT国际专利，PCT/CN2021/093911，2021年5月14日。

12. 基于压缩感知的神经网络模型压缩方法、设备及存储介质，PCT国际专利，WO2022000373A1，2020年7月1日。

13. 视频编码质量平滑度的优化方法、装置、设备及存储介质，PCT国际专利，WO2020042177A1, 2020年3月5日。

近年来，为计算机应用技术专业研究生开设以下两门课程：

1. 《三维视觉与计算摄像学》（Fall Semester，选修）

2. 《现代视频处理专题》（Spring Semester，选修）

对计划招收的硕士和博士研究生的基本要求（点击查看招生要求）：

1. 专业范围：计算机、电子信息、自动化等信息科学类专业的本科和硕士毕业生。

2. 外语/数学能力：英语六级。

3. 研究/开发能力：熟练的程序设计能力，具有一定的探索能力和创新精神。

4. 其他要求：对做科研工作有热情、有兴趣，自我驱动力强。