Object Tracking Using Siamese Network-Based Reinforcement Learning
Object tracking is a technique for tracking a specific object appearing in a video sequence while observing its features or changes. Recently, many algorithms showing high performance have emerged by applying the Siamese network to the object tracking field. A Siamese network is designed to learn th...
Main Authors: | Sung Jun Park, Seung Jun Hwang, Joong-Hwan Baek |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9794996/ |
Similar Items
-
Multi‐template temporal information fusion for Siamese object tracking
by: Xiaofeng Lu, et al.
Published: (2023-02-01) -
Dynamic Siamese Network With Adaptive Kalman Filter for Object Tracking in Complex Scenes
by: Youming Wang, et al.
Published: (2020-01-01) -
Siamese Tracking with Adaptive Template-Updating Strategy
by: Zheng Xu, et al.
Published: (2019-09-01) -
FPSiamRPN: Feature Pyramid Siamese Network With Region Proposal Network for Target Tracking
by: Yunbo Rao, et al.
Published: (2020-01-01) -
Cooperative Use of Recurrent Neural Network and Siamese Region Proposal Network for Robust Visual Tracking
by: Xuechen Zhao, et al.
Published: (2021-01-01)