View Decomposition and Adversarial for Semantic Segmentation | |
He Guan; Zhaoxiang Zhang | |
2018-06 | |
会议日期 | August, 28-31, 2018 |
会议地点 | Nanjing |
关键词 | View Decomposition Adversarial Semantic Segmentation |
英文摘要 | The adversarial training strategy has been effectively validated because it maintains high-level contextual consistency. However, limited to the weak capability of a simple discriminator, it is irresponsible and unreasonable to identify one from the sample source at a time. We introduce a novel discriminator module called Multi-View Decomposition which transforms the discriminator role from general teacher to specific adversary. The proposed module separates single sample into a series of class inter-independent streams and extracts corresponding features from current mask. The key insight in the MVD module is that the final source decision can be aggregated from all available views rather than a harsh critic. Our experimental results demonstrate that the proposed module can improve performance on PASCAL VOC 2012 and PASCAL Context dataset further. |
URL标识 | 查看原文 |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/21599] |
专题 | 自动化研究所_类脑智能研究中心 |
作者单位 | 1.University of Chinese Academy of Sciences 2.Research Center for Brain-inspired Intelligence, CASIA 3.CAS Center for Excellence in Brain Science and Intelligence Technology 4.National Laboratory of Pattern Recognition, CASIA |
推荐引用方式 GB/T 7714 | He Guan,Zhaoxiang Zhang. View Decomposition and Adversarial for Semantic Segmentation[C]. 见:. Nanjing. August, 28-31, 2018. |
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