Manipulation Edge Detection Module

Manipulation edge detection modules focus on identifying and analyzing edges in various data types, including images, graphs, and signals, to improve the accuracy and efficiency of downstream tasks. Current research emphasizes developing efficient algorithms and model architectures, such as graph neural networks and convolutional neural networks, to detect and utilize edge information for tasks ranging from image manipulation detection and graph purification to semantic segmentation and knowledge graph completion. These advancements have significant implications for diverse fields, improving the robustness and fairness of machine learning models, enhancing image and video analysis, and enabling more accurate and efficient data processing in various applications.