Learning Rich Features for Image Manipulation Detection(CVPR 2018 图像篡改检测)
今天来给大家分享一篇CVPR2018的论文，检测图像的篡改区域，用Faster R-CNN网络定位图像被篡改的部分，练就PS检测的火眼金睛。让PS痕迹无处可逃。这就将图像鉴伪，图像取证这方面与深度学习技术结合起来啦。针对这篇论文的分享，做了一个PPT，放到CSDN的下载专区，有论文的PDF（带部分注解），有PPT可修改。下载链接如下https://download.csdn.net/downloa
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- 1. 【篡改检测 2】ManTra-Net: Manipulation Tracing Network For Detection And Localization
- 2. 论文笔记（图像篡改检测）（四）：Forensic Similarity for Digital Images
- 3. 论文笔记(图像篡改检测_CVPR2019)（三）：ManTra-Net: Manipulation Tracing Network
- 4. 《Learning Enriched Features for Real Image Restoration and Enhancement》
- 5. Aggregation of Rich Depth-Aware Features in a Modified Stacked Generalization Model for Single Image
- 6. Learning Rich Features from RGB-D Images for Object Detection and Segmentation(ECCV2014)
- 7. 【论文笔记】：Learning Rich Features at High-Speed for Single-Shot Object Detection
- 8. Learning Rich Features at High-Speed for Single-Shot Object Detection 论文笔记
- 9. 《Learning Rich Features at High-Speed for Single-Shot Object Detection》笔记
- 10. 图像篡改被动检测技术一览：基于特征提取和卷积神经网络的篡改检测