RA-Net: A Deep Learning Approach Based on Residual Structure and Attention Mechanism for Image Copy-Move Forgery Detection. - Kaiqi Zhao 004; Xiaochen Yuan; Zhiyao Xie; Guoheng Huang; Li Feng 001 (ICANN (10), 2023)

SPA-Net: A Deep Learning Approach Enhanced Using a Span-Partial Structure and Attention Mechanism for Image Copy-Move Forgery Detection. - Kaiqi Zhao 004; Xiaochen Yuan; Zhiyao Xie; Yan Xiang; Guoheng Huang; Li Feng 001 (Sensors, 2023)

SCCA-Net: A Novel Network for Image Manipulation Localization Using Split-Channel Contextual Attention. - Yan Xiang; Kaiqi Zhao 004; Haichang Yin (ACCV (7), 2024)

DSTNet: Distinguishing Source and Target Areas for Image Copy-Move Forgery Detection. - Kaiqi Zhao 004; Xiaochen Yuan; Guoheng Huang; Kun Liu (ICPR (22), 2024)

CAMU-Net: Copy-move forgery detection utilizing coordinate attention and multi-scale feature fusion-based up-sampling. - Kaiqi Zhao 004; Xiaochen Yuan; Tong Liu 021; Yan Xiang; Zhiyao Xie; Guoheng Huang; Li Feng 001 (Expert Syst. Appl., 2024)

A Two-Phase Scheme by Integration of Deep and Corner Feature for Balanced Copy-Move Forgery Localization. - Tong Liu 021; Xiaochen Yuan; Zhiyao Xie; Kaiqi Zhao 004; Guoheng Huang; Chi-Man Pun (IEEE Trans. Ind. Informatics, 2025)

Image Manipulation Localization Using Dual-Shallow Feature Pyramid Fusion and Boundary Contextual Incoherence Enhancement. - Yan Xiang; Xiaochen Yuan; Kaiqi Zhao 004; Tong Liu 021; Zhiyao Xie; Guoheng Huang; Jianqing Li 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2025)