Knowledge Commons of Institute of Automation,CAS
High-Performance Discriminative Tracking with Transformers | |
Bin, Yu![]() ![]() ![]() ![]() ![]() | |
2021-10-11 | |
会议名称 | IEEE/CVF International Conference on Computer Vision (ICCV) |
会议日期 | 2021-10-11--2021-10-17 |
会议地点 | online |
出版者 | IEEE |
摘要 | End-to-end discriminative trackers improve the state of the art significantly, yet the improvement in robustness and efficiency is restricted by the conventional discriminative model, i.e., least-squares based regression. In this paper, we present DTT, a novel single-object discriminative tracker, based on an encoder-decoder Transformer architecture. By self- and encoder-decoder attention mechanisms, our approach is able to exploit the rich scene information in an |
DOI | 10.1109/ICCV48922.2021.00971 |
收录类别 | EI |
语种 | 英语 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48791 |
专题 | 紫东太初大模型研究中心_图像与视频分析 |
作者单位 | School of Artificial Intelligence, UCAS, China |
推荐引用方式 GB/T 7714 | Bin, Yu,Ming, Tang,Linyu, Zheng,et al. High-Performance Discriminative Tracking with Transformers[C]:IEEE,2021. |
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 | ||
YuICCV2021.pdf(5421KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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