Image Matting

Image matting is the computational task of separating a foreground object from its background in an image, producing an alpha matte representing the object's transparency. Current research emphasizes improving accuracy and efficiency, particularly through the development of generative models (like diffusion models) and transformer-based architectures, often aiming to reduce reliance on labor-intensive manual annotations (e.g., trimaps) by utilizing weaker supervision or interactive user input. These advancements have significant implications for various applications, including image editing, video production, and augmented reality, by enabling more realistic and efficient compositing and manipulation of digital imagery.