Knowledge Commons of Institute of Automation,CAS
Adaptive Class Suppression Loss for Long-Tail Object Detection | |
Wang, Tong1,2; Zhu, Yousong1,3; Zhao, Chaoyang1; Zeng, Wei4,5; Wang, Jinqiao1,2,6; Tang, Ming1 | |
2021-06 | |
会议名称 | IEEE/CVF Conference on Computer Vision and Pattern Recognition |
页码 | 3103-3112 |
会议日期 | 2021-6-19 |
会议地点 | Online |
摘要 | To address the problem of long-tail distribution for the large vocabulary object detection task, existing methods usually divide the whole categories into several groups and treat each group with different strategies. These methods bring the following two problems. One is the training inconsistency between adjacent categories of similar sizes, |
学科领域 | 模式识别 |
学科门类 | 工学::计算机科学与技术(可授工学、理学学位) |
收录类别 | EI |
资助项目 | National Natural Science Foundation of China (NSFC)[61633002] ; National Natural Science Foundation of China[61806200] ; National Nature Science Foundation of China[61876086] ; National Natural Science Foundation of China[61772527] ; National Natural Science Foundation of China[61772527] ; National Nature Science Foundation of China[61876086] ; National Natural Science Foundation of China[61806200] ; National Natural Science Foundation of China (NSFC)[61633002] |
语种 | 英语 |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/47413 |
专题 | 紫东太初大模型研究中心_图像与视频分析 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 3.ObjectEye Inc., Beijing, China 4.Peking University, Beijing, China 5.Peng Cheng Laboratory, Shenzhen, China 6.NEXWISE Co., Ltd., Guangzhou, China |
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 | Wang, Tong,Zhu, Yousong,Zhao, Chaoyang,et al. Adaptive Class Suppression Loss for Long-Tail Object Detection[C],2021:3103-3112. |
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 | ||
Adaptive Class Suppr(2668KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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