个人简历

张悦，工学博士，讲师。博士毕业于英国萨里大学，曾在北京航空航天大学进行博士后研究。主要从事三维计算机视觉领域的研究，聚焦于多视角匹配和跟踪。近年来，在IEEE TMM、PR、AAAI等国际重要期刊和会议上发表论文多篇。

研究方向

三维计算机视觉、多视角匹配、机器学习

教育经历

2014 - 2017 北京航空航天大学 电子与通信工程 硕士

2017 - 2023 英国萨里大学（University of Surrey） 电子工程 博士

工作经历

2023 - 2026 北京航空航天大学 博士后

学术成果

主要发表论文

[1] Yue Zhang, Mai Xu, Lai Jiang, Xin Deng, Si Liu. A Novel Geometry-Aware Spatio-Temporal Network for Multi-View Video Feature Learning, Pattern Recognition (PR), 2026. (中科院1区Top, IF = 7.6)

[2] Xiaoye Liang, Lai Jiang, Minglang Qiao, Yichen Guo, Yue Zhang*, Xin Deng, Shengxi Li, Yufan Liu, Mai Xu. Burst Image Quality Assessment: A New Benchmark and Unified Framework for Multiple Downstream Tasks, AAAI Conference on Artificial Intelligence (AAAI), 2026, Singapore. (CCF A)

[3] Yue Zhang, Akin Caliskan, Mai Xu, Adrian Hilton, Jean-Yves Guillemaut. MVL-net: Pairwise Learning for Multi-View Multiple People Labelling, IEEE Transactions on Multimedia (TMM), Vol. 27, pp. 4736 – 4751, 2025. (中科院1区Top, IF = 9.7)

[4] Yue Zhang, Mai Xu, Lai Jiang. Consistent Cross-View Association of Aerial-Ground Remote Sensing Imagery via Graph-Constrained Framework, Remote Sensing. (中科院2区, IF = 4.1)

[5] Yue Zhang, Lai Jiang, Mai Xu. A Novel Keypoint-Based Approach for Occlusion Problem in Cross-View Labelling, IEEE International Conference on Signal, Information and Data Processing (ICSIDP), Zhuhai, China, 2024, pp. 1-5.

[6] Yue Zhang, Akin Caliskan, Adrian Hilton, Jean-Yves Guillemaut. A Novel Multi-View Labelling Network Based on Pairwise Learning, IEEE International Conference on Image Processing (ICIP), Anchorage, AK, USA, 2021, pp. 3682-3686. (CCF C)

[7] Yue Zhang, Adrian Hilton, Jean-Yves Guillemaut. A New Approach Combining Trained Single-View Networks with Multi-View Constraints for Robust Multi-View Object Detection and Labelling, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP), Valletta, Malta, 2020.

[8] Yichen Guo, Mai Xu, Lai Jiang, Xin Deng, Yue Zhang, Yufan Liu. Compressed Image Super-resolution based on Invertible Degradation and Restoration, Pattern Recognition (PR), vol. 172, 2025. (中科院1区Top, IF = 7.6)