Knowledge Commons of Institute of Automation,CAS
Nested Collaborative Learning for Long-Tailed Visual Recognition | |
Li J(李俊)1,2; Tan ZC(谭资昌)3,4; Wan J(万军)1,2; Lei Z(雷震)1,2,5; Guo GD(郭国栋)3,4 | |
2023-03 | |
会议名称 | IEEE Conference on Computer Vision and Pattern Recognition (CVPR) |
会议日期 | 2022-6 |
会议地点 | New Orleans Ernest N. Morial Convention Center |
摘要 | The networks trained on the long-tailed dataset vary remarkably, despite the same training settings, which shows the great uncertainty in long-tailed learning. To alleviate the uncertainty, we propose a Nested Collaborative Learning (NCL), which tackles the problem by collaboratively |
收录类别 | EI |
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 | 小样本高噪声数据学习 |
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/173211/57095 |
专题 | 多模态人工智能系统全国重点实验室_生物识别与安全技术 |
通讯作者 | Wan J(万军) |
作者单位 | 1.CBSR&NLPR, Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 3.Institute of Deep Learning, Baidu Research, Beijing, China 4.National Engineering Laboratory for Deep Learning Technology and Application, Beijing, China 5.Centre for Artificial Intelligence and Robotics, Hong Kong Institute of Science&Innovation, Chinese Academy of Sciences, Hong Kong, China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Li J,Tan ZC,Wan J,et al. Nested Collaborative Learning for Long-Tailed Visual Recognition[C],2023. |
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 | ||
Li_Nested_Collaborat(1178KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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