Semantic Image Matting
5 papers with code • 1 benchmarks • 0 datasets
Most implemented papers
Deep Image Matting
We evaluate our algorithm on the image matting benchmark, our testing set, and a wide variety of real images.
Instance Segmentation based Semantic Matting for Compositing Applications
In order to achieve automatic compositing in natural scenes, we propose a fully automated method that integrates instance segmentation and image matting processes to generate high-quality semantic mattes that can be used for image editing task.
Indices Matter: Learning to Index for Deep Image Matting
We show that existing upsampling operators can be unified with the notion of the index function.
Natural Image Matting via Guided Contextual Attention
Inspired by affinity-based method and the successes of contextual attention in inpainting, we develop a novel end-to-end approach for natural image matting with a guided contextual attention module, which is specifically designed for image matting.
Semantic Image Matting
Specifically, we consider and learn 20 classes of matting patterns, and propose to extend the conventional trimap to semantic trimap.