Locate then Segment: A Strong Pipeline for Referring Image Segmentation | |
Jing Y(荆雅)1,2![]() ![]() ![]() ![]() ![]() | |
2021-06 | |
会议名称 | 2021 IEEE Conference on Computer Vision and Pattern Recognition |
会议日期 | 2021-6 |
会议地点 | virtual |
摘要 | Referring image segmentation aims to segment the objects referred by a natural language expression. Previous methods usually focus on designing an implicit and recurrent feature interaction mechanism to fuse the visuallinguistic features to directly generate the final segmentation mask without explicitly modeling the localization information of the referent instances. To tackle these problems, we view this task from another perspective by decoupling it into a "Locate-Then-Segment" (LTS) scheme. Given a language expression, people generally first perform attention to the corresponding target image regions, then generate a |
七大方向——子方向分类 | 图像视频处理与分析 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44447 |
专题 | 模式识别实验室 |
作者单位 | 1.Center for Research on Intelligent Perception and Computing (CRIPAC), National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA) 2.School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS) 3.ByteDance AI Lab |
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 | Jing Y,Kong T,Wang W,et al. Locate then Segment: A Strong Pipeline for Referring Image Segmentation[C],2021. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
2103.16284.pdf(4191KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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