Learn to Match: Automatic Matching Network Design for Visual Tracking

Learn to Match: Automatic Matching Network Design for Visual Tracking

2 August 2021

Bing Li

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Papers citing "Learn to Match: Automatic Matching Network Design for Visual Tracking"

8 / 58 papers shown

Title
Correlation-Aware Deep Tracking Fei Xie Chunyu Wang Guangting Wang Yue Cao Wankou Yang Wenjun Zeng VOT 114 123 0 03 Mar 2022
Guide Local Feature Matching by Overlap Estimation Ying Chen Dihe Huang Shang Xu Jianlin Liu Yang Liu ViT 55 27 0 18 Feb 2022
WebUAV-3M: A Benchmark for Unveiling the Power of Million-Scale Deep UAV Tracking Chunhui Zhang Guanjie Huang Li Liu Shan Huang Yinan Yang Xiang Wan Shiming Ge Dacheng Tao 157 24 0 19 Jan 2022
Learning Target-aware Representation for Visual Tracking via Informative Interactions Mingzhe Guo Zhipeng Zhang Heng Fan L. Jing Yilin Lyu Bing Li Weiming Hu 80 53 0 07 Jan 2022
SwinTrack: A Simple and Strong Baseline for Transformer Tracking Liting Lin Heng Fan Zhipeng Zhang Yong-mei Xu Haibin Ling ViT 116 325 0 02 Dec 2021
VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows Tianlin Li Jianing Li Lin Zhu Zhipeng Zhang Zhe Chen Xin Li Yaowei Wang Yonghong Tian Feng Wu 112 130 0 11 Aug 2021
MFGNet: Dynamic Modality-Aware Filter Generation for RGB-T Tracking Tianlin Li Xiu Shu Shiliang Zhang Bo Jiang Yaowei Wang Yonghong Tian Feng Wu 105 52 0 22 Jul 2021
One More Check: Making "Fake Background" Be Tracked Again Chao Liang Zhipeng Zhang Xue Zhou Bing Li Weiming Hu VOT 74 65 0 19 Apr 2021