Knowledge Commons of Institute of Automation,CAS
UniVIP: A Unified Framework for Self-Supervised Visual Pre-training | |
Li, Zhaowen1,2; Zhu, Yousong1; Yang, Fan3; Li, Wei3; Zhao, Chaoyang1,4; Chen, Yingying1; Chen, Zhiyang1,2; Xie, Jiahao5; Wu, Liwei3; Zhao, Rui3,7; Tang, Ming1; Wang, Jinqiao1,2,6 | |
2022-06 | |
会议名称 | IEEE Computer Vision and Pattern Recognition (CVPR) |
会议日期 | 2022-6-19 |
会议地点 | New Orleans, Louisiana & Online |
摘要 | Self-supervised learning (SSL) holds promise in leveraging large amounts of unlabeled data. However, the success of popular SSL methods has limited on single-centricobject images like those in ImageNet and ignores the correlation among the scene and instances, as well as the semantic difference of instances in the scene. To address the |
收录类别 | EI |
七大方向——子方向分类 | 多模态智能 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/47419 |
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, CAS, Beijing, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China 3.SenseTime Research 4.Development Research Institute of Guangzhou Smart City, Guangzhou, China 5.S-Lab, Nanyang Technological University 6.Peng Cheng Laboratory, Shenzhen, China 7.Qing Yuan Research Institute, Shanghai Jiao Tong University, Shanghai, 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 | Li, Zhaowen,Zhu, Yousong,Yang, Fan,et al. UniVIP: A Unified Framework for Self-Supervised Visual Pre-training[C],2022. |
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 | ||
UniVIP A Unified Fra(1929KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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