Deep Automatic Portrait Matting
Refereed conference paper presented and published in conference proceedings


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其它資訊
摘要We propose an automatic image matting method for portrait images. This method does not need user interaction, which was however essential in most previous approaches. In order to accomplish this goal, a new end-to-end convolutional neural network (CNN) based framework is proposed taking the input of a portrait image. It outputs the matte result. Our method considers not only image semantic prediction but also pixel-level image matte optimization. A new portrait image dataset is constructed with our labeled matting ground truth. Our automatic method achieves comparable results with state-of-the-art methods that require specified foreground and background regions or pixels. Many applications are enabled given the automatic nature of our system.
著者Xiaoyong Shen, Xin Tao, Hongyun Gao, Chao Zhou, Jiaya Jia
會議名稱European Conference on Computer Vision
會議開始日08.10.2016
會議完結日16.10.2016
會議地點Amsterdam
會議國家/地區荷蘭
會議論文集題名ECCV 2016: Computer Vision – ECCV 2016
出版年份2016
卷號9905
出版社Springer
頁次92 - 107
國際標準書號978-3-319-46447-3
電子國際標準書號978-3-319-46448-0
國際標準期刊號0302-9743
語言美式英語

上次更新時間 2022-13-01 於 00:50