Personal Information

I am currently working at Changzhou University, Changzhou, China. I recieved my Ph. D. degree from Xidian University in December 2019. From September 2018 to September 2019, I was funded by CSC as a visiting student in Lancaster University and Warick University.

常州大学，讲师，硕导，2019年于西安电子科技大学获博士学位，2018年9月-2019年9月受国家CSC资助于英国兰卡斯特大学联合培养。

Research Interest

My current research interest convers computer vision and machine learning, including salient object detection, camoufalged object detection, capsule network, 3D poind cloud, etc.

Publication (Google Scholar)

Journal:

2022:

  1. Yang Yang, Qi Qin, Yongjiang Luo, Yi Liu, Qiang Zhang, and Jungong Han, Bi-directional progressive guidance network for RGB-D salient object detection, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), DOI: 10.1109/TCSVT.2022.3144852, 2022.

  2. Qiang Zhang, Mingxing Duanmu, Yongjiang Luo, Yi Liu, and Jungong Han, Engaging part-whole hierarchies and contrast cues for salient object detection, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), DOI: 10.1109/TCSVT.2021.3104932, 2021.

2021-

  1. Yi Liu, Dingwen Zhang, Qiang Zhang, Jungong Han, Part-object relational visual saliency, IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2021, DOI 10.1109/TPAMI.2021.3053577. Code and Result

  2. Yi Liu, Jungong Han, Qiang Zhang, Caifeng Shan, Deep Salient Object Detection with Contextual Information Guidance, IEEE Transactions on Image Processing (T-IP), 2020, 29: 360-374. Code and Result

  3. Yi Liu, Dingwen Zhang, Qiang Zhang, Jungong Han, Integrating part-object relationship and contrast for camouflaged object detection, 2021, IEEE Transactions on Information Forensics and Security (T-IFS), 2021, 16: 5154-5166. Code and Result

  4. Yi Liu, Jungong Han, Qiang Zhang, Long Wang, Salient object detection via two-stage graphs, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 2019, 29(4): 1023-1037. Code Result

  5. Yi Liu, Qiang Zhang, Jungong Han, Long Wang, Salient object detection employing robust sparse representation and local consistency, Image and Vision Computing (IVC), 2018, 69: 155-167. Result

  6. Yi Liu, Jungong Han, Zhen Huo, Qiang Zhang, Exploring multi-scale deformable context and channel-wise attention for salient object detection, Neurocomputing, 2021, 428: 92-103.

  7. Qiang Zhang, Mingxing Duanmu, Yongjiang Luo, Yi Liu, and Jungong Han, Engaging part-whole hierarchies and contrast cues for salient object detection, IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 2021， DOI 10.1109/TCSVT.2021.3104932.

  8. Qiang Zhang, Yi Liu, Rick. S. Blum, Jungong Han, Dacheng Tao, Sparse representation based multi-sensor image fusion for multi-focus and multi-modality images: A review, Information Fusion, 2018, 40: 57-75.

  9. Qiang Zhang, Yi Liu, Siyang Zhu, Jungong Han, Salient object detection based on super-pixel clustering and unified low-rank representation, Computer Vision and Image Understanding (CVIU), 2017, 161: 51-64.

  10. Nianchang Huang, Yi Liu, Qiang Zhang, Jungong Han, Joint cross-modal and unimodal features for RGB-D salient object detection, IEEE Transactions on Multimedia (T-MM), 2020, 23: 2428-2440.

  11. Qiang Zhang, Zhen Huo, Yi Liu, Yunhui Pan, Caifeng Shan, Jungong Han, Salient object detection employing a local tree-structured low-rank representation and foreground consistency, Pattern Recognition (PR), 2019, 92: 119-134.

Conference:

  1. Yi Liu, Qiang Zhang, Dingwen Zhang, Jungong Han, Employing Deep Part-Object Relationships for Salient Object Detection, IEEE International Conference on Computer Vision (ICCV), 1232-1241, 2019. Code and Result

Grants

  1. 国家自然科学基金青年科学项目，基于轻量化胶囊网络的图像显著目标检测，64211341，主持，2021.01.01-2023.12.31

  2. 江苏省自然科学基金面上项目，部件-整体关系启发的统一视觉注意目标检测研究，主持，2022.07.01-2025.06.30

Patent

  1. 张强，刘毅，关永强，霍臻，王龙，基于鲁棒稀疏表示与拉普拉斯正则项的显著目标检测方法，专利号：ZL201710419857.0，授权日期：2019.08.06

  2. 张强，刘毅，姚琳，韩军功，王龙，基于细化空间一致性二阶段图的显著目标检测方法，授权日期：2021.05.04

  3. 刘毅，顾佳楠，徐守坤，基于解缠胶囊路由的部分-目标关系显著目标检测方法，申请日期：2022.05.13

Award

  1. 2016年度“中国电子科技集团公司-西安电子科技大学协同创新奖学金”一等奖（学院排名第一），2018年

  2. 博士研究生国家奖学金，2017年，

  3. 西安电子科技大学优秀研究生，2017年

Activity

Reviewer of IEEE T-IP, IEEE T-CSVT, ACCV, etc.