Learning Trimaps via Clicks for Image Matting

Despite the significant advancements achieved in image matting, the existing models heavily depend on manually drawn trimaps to produce accurate results in natural image scenarios. However, the process of obtaining trimaps is time-consuming and lacks user-friendliness and device compatibility. This greatly limits the practical applicability of all trimap-based matting methods. To address this issue, we introduce <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Click2Trimap</b>, an interactive model that is capable of predicting high-quality trimaps and alpha mattes with minimal user click inputs. By analyzing real users’ behavioral logic and the characteristics of trimaps, we successfully propose a powerful iterative three-class training strategy and a dedicated simulation function, making Click2Trimap exhibit versatility across various scenarios. Compared with all existing trimap-free matting methods, Click2Trimap achieves superior performance in quantitative and qualitative assessments conducted on synthetic and real-world matting datasets. In particular, in a user study, Click2Trimap yields high-quality trimap and matting predictions in just 5 seconds per image on average, demonstrating its substantial practical value for use in real-world applications.