  Despite significant advancements in image matting, existing models heavily
depend on manually-drawn trimaps for accurate results in natural image
scenarios. However, the process of obtaining trimaps is time-consuming, lacking
user-friendliness and device compatibility. This reliance greatly limits the
practical application of all trimap-based matting methods. To address this
issue, we introduce Click2Trimap, an interactive model capable of predicting
high-quality trimaps and alpha mattes with minimal user click inputs. Through
analyzing real users' behavioral logic and 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. Quantitative and qualitative assessments on synthetic and
real-world matting datasets demonstrate Click2Trimap's superior performance
compared to all existing trimap-free matting methods. Especially, in the user
study, Click2Trimap achieves high-quality trimap and matting predictions in
just an average of 5 seconds per image, demonstrating its substantial practical
value in real-world applications.
