SeqTrack: Sequence to Sequence Learning for Visual Object Tracking-Reference-Cited by-同舟云学术

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SeqTrack: Sequence to Sequence Learning for Visual Object Tracking

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
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Author:

Chen Xin¹,Peng Houwen²,Wang Dong¹,Lu Huchuan¹,Hu Han²

Affiliation:

1. Dalian University of Technology

2. Microsoft Research

Funder

National Natural Science Foundation of China (NSFC)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203645.pdf?arnumber=10203645

Reference58 articles.

1. Probabilistic Regression for Visual Tracking

2. Learn to Match: Automatic Matching Network Design for Visual Tracking

3. ATOM: Accurate Tracking by Overlap Maximization

4. Deformable Siamese Attention Networks for Visual Object Tracking

5. LaSOT: A High-quality Large-scale Single Object Tracking Benchmark

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2. Dual-branch collaborative Siamese network for visual tracking;Digital Signal Processing;2024-12

3. MIMTracking: Masked image modeling enhanced vision transformer for visual object tracking;Neurocomputing;2024-11

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