Generate Fake Image and Detection

Generate Fake Image and Detection

Generate Fake Image

• 【深圳大学】深度文档图像伪造

  L. Zhao, C. Chen and J. Huang, “Deep Learning-based Forgery Attack on Document Images”, IEEE Transactions on Image Processing, Accepted Aug. 2021

Fake Image Detection

• 生成内容取证：基于自注意力机制的GAN生成图像检测算法

  [JSTSP, 2020] Mi, Z., Jiang, X., Sun, T., & Xu, K. (2020). GAN-Generated Image Detection With Self-Attention Mechanism Against GAN Generator Defect. IEEE Journal of Selected Topics in Signal Processing, 14(5), 969–981.

• 针对数字图像中复制粘贴篡改的定位取证新方法

  [IEEE TMM, 2020] Beijing Chen, Weijin Tan, Gouenou Coatrieux, Yuhui Zheng, and Yun-Qing Shi, “A serial image copy-move forgery localization scheme with source/target distinguishment,” IEEE Transactions on Multimedia. 2020. Online. DOI: 10.1109/TMM.2020.3026868.

• 社交网络压缩深伪视频检测

  Juan Hu, Xin Liao, Wei Wang, and Zheng Qin, “Detecting compressedDeepfake videos in social networks using frame-temporality two-streamconvolutional network”, IEEE Transactionson Circuits and Systems for Video Technology, DOI:10.1109/TCSVT.2021.3074259, 2021.

• 基于神经架构搜索和感知模块的图像修复取证

  H. Wu and J. Zhou, "GIID-Net: Image Inpainting Detection Network via Neural Architecture Search and Attention," in IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2021.3075039.

• 深度伪造视频检测：基于时域剔除3DCNN的方法

  Daichi Zhang, Chenyu Li, Fanzhao Lin, Dan Zeng, Shiming Ge*. Detecting Deepfake Videos with Temporal Dropout 3DCNN. Accepted by International Joint Conference on Artificial Intelligence (IJCAI), 2021.

• 从数字图像到免疫图像

  Q Ying, Z Qian*, HZhou, X Zhang, H Xu, S Li,From Image to Imuge: Immunized ImageGeneration, ACM multimedia 2021

  感觉这篇的结果很有意思，可能会成为研究的点。

• 抗压缩的伪造人脸图像检测

  Cao, S., Zou, Q., Mao, X., & Wang, Z. (2021). Metric Learning for Anti-Compression Facial Forgery Detection. http://arxiv.org/abs/2103.08397

• 基于自监督领域自适应的JPEG压缩图像篡改定位方法

  Y. Rao, and J. Ni, “Self-supervised Domain Adaptation for Forgery Localization of JPEG Compressed Images,” IEEE International Conference on Computer Vision (ICCV), Oral, 2021.

• CAT-NET
  Kwon, M.-J., Nam, S.-H., Yu, I.-J., Lee, H.-K., & Kim, C. (2021). Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization. http://arxiv.org/abs/2108.12947

Image Inpainting

• 基于图像重建探究SIFT特征的隐私泄漏

  H. Wu and J. Zhou, "Privacy Leakage of SIFT Features via Deep Generative Model Based Image Reconstruction," in IEEE Transactions on Information Forensics and Security, vol. 16, pp. 2973-2985, 2021, doi: 10.1109/TIFS.2021.3070427.