Search Results for author:
Found 6 papers, 2 papers with code
Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization
It significantly outperforms traditional and deep neural network-based methods in detecting and localizing tampered regions.
Ranked #3 on
Image Manipulation Detection
on Casia V1+
Frame-rate Up-conversion Detection Based on Convolutional Neural Network for Learning Spatiotemporal Features
The proposed network uses a stack of consecutive frames as the input and effectively learns interpolation artifacts using network blocks to learn spatiotemporal features.
Deep Convolutional Neural Network for Identifying Seam-Carving Forgery
Seam carving is a representative content-aware image retargeting approach to adjust the size of an image while preserving its visually prominent content.
BitMix: Data Augmentation for Image Steganalysis
Convolutional neural networks (CNN) for image steganalysis demonstrate better performances with employing concepts from high-level vision tasks.
Double JPEG Detection in Mixed JPEG Quality Factors using Deep Convolutional Neural Network
Double JPEG detection is essential for detecting various image manipulations.
Learning deep features for source color laser printer identification based on cascaded learning
Color laser printers have fast printing speed and high resolution, and forgeries using color laser printers can cause significant harm to society.
