Differential Reinforcement and Global Collaboration Network for RGBT Tracking
Author:
Affiliation:
1. School of Information Science and Engineering, Yunnan University, Kunming, China
2. School of Mathematics, Southeast University, Nanjing, China
Funder
National Natural Science Foundation of China
Yunnan Province University Key Laboratory Construction Plan Funding, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Instrumentation
Link
http://xplorestaging.ieee.org/ielx7/7361/10089784/10048756.pdf?arnumber=10048756
Reference56 articles.
1. Weighted Sparse Representation Regularized Graph Learning for RGB-T Object Tracking
2. Robust Collaborative Discriminative Learning for RGB-Infrared Tracking
3. Dense Feature Aggregation and Pruning for RGBT Tracking
4. Cross-Modal Ranking with Soft Consistency and Noisy Labels for Robust RGB-T Tracking
5. Fusing two-stream convolutional neural networks for RGB-T object tracking
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