Knowledge Commons of Institute of Automation,CAS
A Multi-modal Global Instance Tracking Benchmark (MGIT): Better Locating Target in Complex Spatio-temporal and causal Relationship | |
Shiyu, Hu1,2; Dailing, Zhang1,2; Meiqi, Wu3; Xiaokun, Feng1,2; Xuchen, Li4; Xin, Zhao1,2; Kaiqi, Huang1,2,5 | |
2023-12 | |
会议名称 | the 37th Conference on Neural Information Processing Systems |
会议日期 | 2023-12 |
会议地点 | New Orleans |
摘要 | Tracking an arbitrary moving target in a video sequence is the foundation for high-level tasks like video understanding. Although existing visual-based trackers have demonstrated good tracking capabilities in short video sequences, they always perform poorly in complex environments, as represented by the recently proposed global instance tracking task, which consists of longer videos with more complicated narrative content. |
收录类别 | EI |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
国重实验室规划方向分类 | 智能能力评估 |
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/173211/54537 |
专题 | 复杂系统认知与决策实验室_智能系统与工程 |
作者单位 | 1.School of Artificial Intelligence, University of Chinese Academy of Sciences 2.Institute of Automation, Chinese Academy of Sciences 3.School of Computer Science and Technology, University of Chinese Academy of Sciences 4.School of Computer Science, Beijing University of Posts and Telecommunications 5.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Shiyu, Hu,Dailing, Zhang,Meiqi, Wu,et al. A Multi-modal Global Instance Tracking Benchmark (MGIT): Better Locating Target in Complex Spatio-temporal and causal Relationship[C],2023. |
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 | ||
MGIT.pdf(6215KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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