Knowledge Commons of Institute of Automation,CAS
Knowledge Mining and Transferring for Domain Adaptive Object Detection | |
Tian Kun1,2![]() ![]() ![]() ![]() | |
2021-10 | |
会议名称 | 2021 IEEE International Conference on Computer Vision |
会议日期 | 2021-10 |
会议地点 | Virtual Conference |
出版者 | IEEE |
摘要 | With the thriving of deep learning, CNN-based object detectors have made great progress in the past decade. However, the domain gap between training and testing data leads to a prominent performance degradation and thus hinders their application in the real world. To alleviate this problem, Knowledge Transfer Network (KTNet) is proposed as a new paradigm for domain adaption. Specifically, KTNet is constructed on a base detector with intrinsic knowledge mining and relational knowledge constraints. First, we design a foreground/background classifier shared by source domain and target domain to extract the common attribute knowledge of objects in different scenarios. Second, we model the relational knowledge graph and explicitly constrain the consistency of category correlation under source domain, target domain, as well as cross-domain conditions. As a result, the detector is guided to learn object-related and domain-independent representation. Extensive experiments and visualizations confirm that transferring object-specific knowledge can yield notable performance gains. The proposed KTNet achieves state-of-the-art results on three cross-domain detection benchmarks. |
收录类别 | EI |
语种 | 英语 |
七大方向——子方向分类 | 图像视频处理与分析 |
国重实验室规划方向分类 | 视觉信息处理 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/56531 |
专题 | 多模态人工智能系统全国重点实验室 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Tian Kun,Zhang Chenghao,Wang Ying,et al. Knowledge Mining and Transferring for Domain Adaptive Object Detection[C]:IEEE,2021. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Tian_Knowledge_Minin(1462KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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