Mask Processing

Mask processing in image and video editing focuses on precisely manipulating specific regions of an image or video frame, often guided by user input or automatically generated masks. Current research emphasizes developing methods that leverage diffusion models and other deep learning architectures to achieve high-fidelity edits while preserving the integrity of unedited regions, often using techniques like disentangled prompt control or auxiliary tasks to improve accuracy and semantic understanding. These advancements are improving the quality and versatility of image and video editing applications, impacting fields such as medical image analysis, anomaly detection, and creative content generation.