Copy Paste

Copy-paste, a simple yet powerful data augmentation technique, is being refined to improve the performance and robustness of various computer vision and software engineering tasks. Current research focuses on context-aware and perspective-aware variations, leveraging models like YOLO and Segment Anything Model (SAM) to enhance realism and address inconsistencies in generated data. These advancements are particularly impactful for applications with limited training data, such as medical image segmentation, road damage detection, and object detection in aerial or crowded scenes, improving model accuracy and efficiency. Furthermore, research extends to code adaptation, where copy-paste techniques are being studied to improve the efficiency and safety of code reuse.