mlsanityData to 14 Oct 2026

VIFB: A Visible and Infrared Image Fusion Benchmark

arXiv 2002.03322 ↗First posted 9 Feb 2020cs.CV cs.MMcited by 25

Not on the map. Why?

Abstract (arXiv)

Visible and infrared image fusion is one of the most important areas in image processing due to its numerous applications. While much progress has been made in recent years with efforts on developing fusion algorithms, there is a lack of code library and benchmark which can gauge the state-of-the-art. In this paper, after briefly reviewing recent advances of visible and infrared image fusion, we present a visible and infrared image fusion benchmark (VIFB) which consists of 21 image pairs, a code library of 20 fusion algorithms and 13 evaluation metrics. We also carry out large scale experiments within the benchmark to understand the performance of these algorithms. By analyzing qualitative and quantitative results, we identify effective algorithms for robust image fusion and give some observations on the status and future prospects of this field.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Feb 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 4; 2024: 6; 2025: 5; 2026: 4.

25 papers.

Sort:

By area:

  1. 2022Target-aware Dual Adversarial Learning and a Multi-scenario Multi-Modality Benchmark to Fuse Infrared and Visible for Object Detectioncited by 317
  2. 2025Infrared and Visible Image Fusion: From Data Compatibility to Task Adaptioncited by 46
  3. 2025Every SAM Drop Counts: Embracing Semantic Priors for Multi-Modality Image Fusion and Beyondcited by 35
  4. 2024MaeFuse: Transferring Omni Features with Pretrained Masked Autoencoders for Infrared and Visible Image Fusion via Guided Trainingcited by 15
  5. 2024FCDFusion: a Fast, Low Color Deviation Method for Fusing Visible and Infrared Image Pairscited by 14
  6. 2024Conditional Controllable Image Fusioncited by 13
  7. 2024Instruction-Driven Fusion of Infrared-Visible Images: Tailoring for Diverse Downstream Taskscited by 9
  8. 2022ROMA: Cross-Domain Region Similarity Matching for Unpaired Nighttime Infrared to Daytime Visible Video Translationcited by 5
  9. 2023A Multi-scale Information Integration Framework for Infrared and Visible Image Fusioncited by 5
  10. 2026Bridging Human Evaluation to Infrared and Visible Image Fusioncited by 4
  11. 2023ShadowSense: Unsupervised Domain Adaptation and Feature Fusion for Shadow-Agnostic Tree Crown Detection from RGB-Thermal Drone Imagerycited by 2
  12. 2022Multimodal Image Fusion based on Hybrid CNN-Transformer and Non-local Cross-modal Attentioncited by 1
13 more
  1. 2024FusionSAM: Visual Multi-Modal Learning with Segment Anythingcited by 1
  2. 2024Visible and Infrared Image Fusion Using Encoder-Decoder Networkcited by 1
  3. 2026Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusioncited by 1
  4. 2021Certifiable Artificial Intelligence Through Data Fusioncited by 0
  5. 2021Physics Driven Deep Retinex Fusion for Adaptive Infrared and Visible Image Fusioncited by 0
  6. 2022Explicit and implicit models in infrared and visible image fusioncited by 0
  7. 2023Self-Supervised RGB-T Tracking with Cross-Input Consistencycited by 0
  8. 2023Fusion of Infrared and Visible Images based on Spatial-Channel Attentional Mechanismcited by 0
  9. 2025MultiTaskVIF: Segmentation-oriented visible and infrared image fusion via multi-task learningcited by 0
  10. 2025Causality-Driven Infrared and Visible Image Fusioncited by 0
  11. 2025SSVIF: Self-Supervised Segmentation-Oriented Visible and Infrared Image Fusioncited by 0
  12. 2026EPOFusion: Exposure aware Progressive Optimization Method for Infrared and Visible Image Fusioncited by 0
  13. 2026Multimodal Object Detection Under Sparse Forest-Canopy Occlusioncited by 0