trimapfree
Trimap-free refers to a class of image matting methods that estimate an alpha matte without requiring a user-provided trimap. In image matting, the alpha matte encodes per-pixel foreground opacity, guiding accurate foreground extraction and compositing onto new backgrounds. Trimap-free approaches aim to infer this matte directly from a single RGB image, reducing user input and enabling more automated editing workflows.
Traditional matting relies on a trimap that marks definite foreground, definite background, and an unknown region
Most trimap-free methods are deep learning based, employing encoder–decoder or transformer architectures to predict the alpha
Common evaluation metrics include Mean Absolute Error (MAE), gradient error, and SAD (sum of absolute differences).
Trimap-free matting is an active area of research in image editing and computer vision, offering automation