Hancheng Zhu (祝汉城)

Associate Professor

School of Computer Science and Technology
China University of Mining and Technology
Xuzhou, Jiangsu, China, 221116

zhuhancheng[at]cumt.edu.cn

Welcome

I am a Postdoctoral Fellow in the School of Computer Science and Technology, China University of Mining and Technology, China. I received the M.S. and Ph.D. degrees from China University of Mining and Technology, Xuzhou, China, in 2015 and 2020, respectively. My research interests are primarily on image aesthetic quality assessment and affective computing.

News

2021.10: One paper is accepted to IEEE Transactions on Multimedia (TMM 2021) 2021.08: I am supported by Natural Science Foundation of China (2022.01-2024.12) 2021.06: I am supported by Natural Science Foundation of Jiangsu Province (2021.07-2024.06) 2021.05: One paper is accepted to Journal of image and Graphics (中国图象图形学报 2021) 2021.04: One paper is accepted to IEEE Transactions on Circuits and Systems for Video Technology (TCSVT 2021) 2020.06: One paper is accepted to IEEE Transactions on Cybernetics (TCYB 2020) 2020.02: One paper is accepted to IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020) 2020.01: One paper is accepted to IEEE Transactions on Image Processing (TIP 2020)

Reviewer

  • TIP, TNNLS, TMM, TIM, JVCI

Representative Publications[Google Scholor]

Journal Papers

Learning Personalized Image Aesthetics from Subjective and Objective Attributes

Hancheng Zhu, Yong Zhou, Leida Li, Yaqian Li, and Yandong Guo
IEEE Transactions on Multimedia (CCF-B, Q1) (TMM), 2021 [accepted].

Generalizable No-Reference Image Quality Assessment via Deep Meta-learning

Hancheng Zhu, Leida Li, Jinjian Wu, Weisheng Dong, and Guangming Shi
IEEE Transactions on Circuits and Systems for Video Technology (CCF-B, Q1) (TCSVT), 2021 [accepted].

Personalized Image Aesthetics Assessment via Meta-Learning With Bilevel Gradient Optimization

Hancheng Zhu, Leida Li, Jinjian Wu, Sicheng Zhao, Guiguang Ding, and Guangming Shi
IEEE Transactions on Cybernetics (CCF-B, Q1) (TCYB), 2020 [accepted].

Personality-Assisted Multi-Task Learning for Generic and Personalized Image Aesthetics Assessment

Leida Li, Hancheng Zhu*, Sicheng Zhao, Guiguang Ding, and Weisi Lin
IEEE Transactions on Image Processing (CCF-A, Q1) (TIP), 2020.

Inferring Personality Traits from Attentive Regions of User Liked Images Via Weakly Supervised Dual Convolutional Network

Hancheng Zhu, Leida Li, Hongyan Jiang, and Allen Tan
Neural Processing Letters (CCF-C, Q2) (NPL), 2020.

Evaluating Attributed Personality Traits from Scene Perception Probability

Hancheng Zhu, Leida Li, Sicheng Zhao, and Hongyan Jiang
Pattern Recognition Letters (CCF-C, Q2) (PRL), 2018.

Conference Papers

MetaIQA: Deep Meta-Learning for No-Reference Image Quality Assessment

Hancheng Zhu, Leida Li, Jinjian Wu, Weisheng Dong, Guangming Shi
IEEE Conference on Computer Vision and Pattern Recognition (CCF-A) (CVPR), Jun. 2020.

Personality Driven Multi-task Learning for Image Aesthetic Assessment

Leida Li, Hancheng Zhu*, Sicheng Zhao, Guiguang Ding, Hongyan Jiang, and Allen Tan
IEEE International Conference on Multimedia and Expo (CCF-B, Oral) (ICME), Jul. 2019.