mlsanityData to 7 Oct 2026

A Survey for Deep RGBT Tracking

arXiv 2201.09296 ↗First posted 23 Jan 2022cs.CVcited by 6

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Abstract (arXiv)

Visual object tracking with the visible (RGB) and thermal infrared (TIR) electromagnetic waves, shorted in RGBT tracking, recently draws increasing attention in the tracking community. Considering the rapid development of deep learning, a survey for the recent deep neural network based RGBT trackers is presented in this paper. Firstly, we give brief introduction for the RGBT trackers concluded into this category. Then, a comparison among the existing RGBT trackers on several challenging benchmarks is given statistically. Specifically, MDNet and Siamese architectures are the two mainstream frameworks in the RGBT community, especially the former. Trackers based on MDNet achieve higher performance while Siamese-based trackers satisfy the real-time requirement. In summary, since the large-scale dataset LasHeR is published, the integration of end-to-end framework, e.g., Siamese and Transformer, should be further considered to fulfil the real-time as well as more robust performance. Furthermore, the mathematical meaning should be more considered during designing the network. This survey can be treated as a look-up-table for researchers who are concerned about RGBT tracking.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 19 of its 51 references that are in the map. First posted on arXiv 23 Jan 2022.

Builds on

19 of 51 references.

References · 19

  1. 2017Attention Is All You Needcited by 59,932
  2. 2016Fully-Convolutional Siamese Networks for Object Trackingcited by 566
  3. 2018GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wildcited by 471
  4. 2018SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networkscited by 445
  5. 2019Learning Discriminative Model Prediction for Trackingcited by 344
  6. 2015Learning Multi-Domain Convolutional Neural Networks for Visual Trackingcited by 209
  7. 2018RGB-T Object Tracking:Benchmark and Baselinecited by 121
  8. 2021LasHeR: A Large-scale High-diversity Benchmark for RGBT Trackingcited by 94
  9. 2019Multi-Modal Fusion for End-to-End RGB-T Trackingcited by 63
  10. 2020NestFuse: An Infrared and Visible Image Fusion Architecture based on Nest Connection and Spatial/Channel Attention Modelscited by 62
  11. 2020Challenge-Aware RGBT Trackingcited by 53
  12. 2020Jointly Modeling Motion and Appearance Cues for Robust RGB-T Trackingcited by 47
7 more
  1. 2019Dense Feature Aggregation and Pruning for RGBT Trackingcited by 40
  2. 2019Multi-Adapter RGBT Trackingcited by 38
  3. 2020RGBT Tracking via Multi-Adapter Network with Hierarchical Divergence Losscited by 32
  4. 2018Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Trackingcited by 25
  5. 2018Multi-focus Image Fusion using dictionary learning and Low-Rank Representationcited by 17
  6. 2019Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Trackingcited by 17
  7. 2017Face Detection, Bounding Box Aggregation and Pose Estimation for Robust Facial Landmark Localisation in the Wildcited by 7

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Cited by year

Citing papers per year: 2023: 3; 2024: 2; 2025: 1.

6 papers.

  1. 2023RGB-T Tracking via Multi-Modal Mutual Prompt Learningcited by 8
  2. 2023RGB-T Tracking Based on Mixed Attentioncited by 7
  3. 2024Awesome Multi-modal Object Trackingcited by 7
  4. 2025Omni Survey for Multimodality Analysis in Visual Object Trackingcited by 2
  5. 2024Middle Fusion and Multi-Stage, Multi-Form Prompts for Robust RGB-T Trackingcited by 1
  6. 2023EANet: Enhanced Attribute-based RGBT Tracker Networkcited by 0