PP-Matting: High-Accuracy Natural Image Matting

Guowei Chen; Yi Liu; Jian Wang; Juncai Peng; Yuying Hao; Lutao Chu; Shiyu Tang; Zewu Wu; Zeyu Chen; Zhiliang Yu; Yuning Du; Qingqing Dang; Xiaoguang Hu; Dianhai Yu

arXiv · 2204.09433

PP-Matting: High-Accuracy Natural Image Matting

Guowei Chen·Yi Liu·Jian Wang·Juncai Peng·Yuying Hao·Lutao Chu·Shiyu Tang·Zewu Wu·Zeyu Chen·Zhiliang Yu·Yuning Du·Qingqing Dang·Xiaoguang Hu·Dianhai Yu

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Abstract

Natural image matting is a fundamental and challenging computer vision task. It has many applications in image editing and composition. Recently, deep learning-based approaches have achieved great improvements in image matting. However, most of them require a user-supplied trimap as an auxiliary input, which limits the matting applications in the real world. Although some trimap-free approaches have been proposed, the matting quality is still unsatisfactory compared to trimap-based ones. Without the trimap guidance, the matting models suffer from foreground-background ambiguity easily, and also generate blurry details in the transition area. In this work, we propose PP-Matting, a trimap-free architecture that can achieve high-accuracy natural image matting. Our method applies a high-resolution detail branch (HRDB) that extracts fine-grained details of the foreground with keeping feature resolution unchanged. Also, we propose a semantic context branch (SCB) that adopts a semantic segmentation subtask. It prevents the detail prediction from local ambiguity caused by semantic context missing. In addition, we conduct extensive experiments on two well-known benchmarks: Composition-1k and Distinctions-646. The results demonstrate the superiority of PP-Matting over previous methods. Furthermore, we provide a qualitative evaluation of our method on human matting which shows its outstanding performance in the practical application. The code and pre-trained models will be available at PaddleSeg: https://github.com/PaddlePaddle/PaddleSeg.

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Guowei Chen, Yi Liu, Jian Wang, Juncai Peng, Yuying Hao, Lutao Chu, Shiyu Tang, Zewu Wu, Zeyu Chen, Zhiliang Yu, Yuning Du, Qingqing Dang, Xiaoguang Hu, Dianhai Yu. 2022-04-20. PP-Matting: High-Accuracy Natural Image Matting. https://arxiv.org/abs/2204.09433

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