Edge Guided Self-correction Skin Detection
Skin detection has been a widely studied computer vision topic for many years,whereas remains a challenging task.Previous methods celebrate their success in various ordinary scenarios but still suffer from fragmentary prediction and poor generalization.To address this issue,this paper proposes an ed...
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| Format: | Article |
| Language: | zho |
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Editorial office of Computer Science
2022-11-01
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| Series: | Jisuanji kexue |
| Subjects: | |
| Online Access: | https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-11-141.pdf |
| _version_ | 1797845108417101824 |
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| author | ZHENG Shun-yuan, HU Liang-xiao, LYU Xiao-qian, SUN Xin, ZHANG Sheng-ping |
| author_facet | ZHENG Shun-yuan, HU Liang-xiao, LYU Xiao-qian, SUN Xin, ZHANG Sheng-ping |
| author_sort | ZHENG Shun-yuan, HU Liang-xiao, LYU Xiao-qian, SUN Xin, ZHANG Sheng-ping |
| collection | DOAJ |
| description | Skin detection has been a widely studied computer vision topic for many years,whereas remains a challenging task.Previous methods celebrate their success in various ordinary scenarios but still suffer from fragmentary prediction and poor generalization.To address this issue,this paper proposes an edge guided network driven by a massive self-corrected skin detection dataset for robust skin detection.To be specific,a multi-task learning based network which conducts skin detection and edge detection jointly is proposed.The predicted edge map is further converged to the skin detection stream via an edge attention module.Meanwhile,to engage a large-scale of low-quality data from the human parsing task to strengthen the generalization of the network,a self-correction algorithm is adapted to prune the side effect of supervised by noisy labels with continuously polishing up those defects during the training process.Experimental results indicate that the proposed method outperforms the state-of-the-art in skin detection. |
| first_indexed | 2024-04-09T17:33:13Z |
| format | Article |
| id | doaj.art-10559e88cebc44cbb3e4f8b7ff909e45 |
| institution | Directory Open Access Journal |
| issn | 1002-137X |
| language | zho |
| last_indexed | 2024-04-09T17:33:13Z |
| publishDate | 2022-11-01 |
| publisher | Editorial office of Computer Science |
| record_format | Article |
| series | Jisuanji kexue |
| spelling | doaj.art-10559e88cebc44cbb3e4f8b7ff909e452023-04-18T02:32:50ZzhoEditorial office of Computer ScienceJisuanji kexue1002-137X2022-11-01491114114710.11896/jsjkx.220600012Edge Guided Self-correction Skin DetectionZHENG Shun-yuan, HU Liang-xiao, LYU Xiao-qian, SUN Xin, ZHANG Sheng-ping0College of Computer Science and Technology,Harbin Institute of Technology,Weihai,Shandong 264209,ChinaSkin detection has been a widely studied computer vision topic for many years,whereas remains a challenging task.Previous methods celebrate their success in various ordinary scenarios but still suffer from fragmentary prediction and poor generalization.To address this issue,this paper proposes an edge guided network driven by a massive self-corrected skin detection dataset for robust skin detection.To be specific,a multi-task learning based network which conducts skin detection and edge detection jointly is proposed.The predicted edge map is further converged to the skin detection stream via an edge attention module.Meanwhile,to engage a large-scale of low-quality data from the human parsing task to strengthen the generalization of the network,a self-correction algorithm is adapted to prune the side effect of supervised by noisy labels with continuously polishing up those defects during the training process.Experimental results indicate that the proposed method outperforms the state-of-the-art in skin detection.https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-11-141.pdfskin detection|edge detection|multi-task learning|self-correction algorithm |
| spellingShingle | ZHENG Shun-yuan, HU Liang-xiao, LYU Xiao-qian, SUN Xin, ZHANG Sheng-ping Edge Guided Self-correction Skin Detection Jisuanji kexue skin detection|edge detection|multi-task learning|self-correction algorithm |
| title | Edge Guided Self-correction Skin Detection |
| title_full | Edge Guided Self-correction Skin Detection |
| title_fullStr | Edge Guided Self-correction Skin Detection |
| title_full_unstemmed | Edge Guided Self-correction Skin Detection |
| title_short | Edge Guided Self-correction Skin Detection |
| title_sort | edge guided self correction skin detection |
| topic | skin detection|edge detection|multi-task learning|self-correction algorithm |
| url | https://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2022-49-11-141.pdf |
| work_keys_str_mv | AT zhengshunyuanhuliangxiaolyuxiaoqiansunxinzhangshengping edgeguidedselfcorrectionskindetection |