mlsanityData to 14 Oct 2026

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

arXiv 2108.10831 ↗First posted 24 Aug 2021cs.CV cs.AIcited by 231

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Abstract (arXiv)

It is very challenging for various visual tasks such as image fusion, pedestrian detection and image-to-image translation in low light conditions due to the loss of effective target areas. In this case, infrared and visible images can be used together to provide both rich detail information and effective target areas. In this paper, we present LLVIP, a visible-infrared paired dataset for low-light vision. This dataset contains 30976 images, or 15488 pairs, most of which were taken at very dark scenes, and all of the images are strictly aligned in time and space. Pedestrians in the dataset are labeled. We compare the dataset with other visible-infrared datasets and evaluate the performance of some popular visual algorithms including image fusion, pedestrian detection and image-to-image translation on the dataset. The experimental results demonstrate the complementary effect of fusion on image information, and find the deficiency of existing algorithms of the three visual tasks in very low-light conditions. We believe the LLVIP dataset will contribute to the community of computer vision by promoting image fusion, pedestrian detection and image-to-image translation in very low-light applications. The dataset is being released in https://bupt-ai-cz.github.io/LLVIP. Raw data is also provided for further research such as image registration.

Key facts. Cited by 231 papers in the map (data through 14 Oct 2026). Builds on 7 of its 23 references that are in the map. First posted on arXiv 24 Aug 2021.

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7 of 23 references.

References · 7

  1. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  2. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
  3. 2018YOLOv3: An Incremental Improvementcited by 2,659
  4. 2014Conditional Generative Adversarial Netscited by 2,162
  5. 2020YOLOv4: Optimal Speed and Accuracy of Object Detectioncited by 1,630
  6. 2016YOLO9000: Better, Faster, Strongercited by 1,431
  7. 2018DenseFuse: A Fusion Approach to Infrared and Visible Imagescited by 180

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 4; 2023: 30; 2024: 47; 2025: 73; 2026: 76.

231 papers.

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  1. 2023ImageBind: One Embedding Space To Bind Them Allcited by 1,175
  2. 2023LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignmentcited by 370
  3. 2024MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?cited by 292
  4. 2023Foundational Models Defining a New Era in Vision: A Survey and Outlookcited by 110
  5. 2021Cross-Modality Fusion Transformer for Multispectral Object Detectioncited by 86
  6. 2024Text-IF: Leveraging Semantic Text Guidance for Degradation-Aware and Interactive Image Fusioncited by 84
  7. 2024Fusion-Mamba for Cross-modality Object Detectioncited by 67
  8. 2022BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pixcited by 61
  9. 2024Task-Customized Mixture of Adapters for General Image Fusioncited by 59
  10. 2023Multi-modal Gated Mixture of Local-to-Global Experts for Dynamic Image Fusioncited by 54
  11. 2024UniBind: LLM-Augmented Unified and Balanced Representation Space to Bind Them Allcited by 49
  12. 2025Infrared and Visible Image Fusion: From Data Compatibility to Task Adaptioncited by 46
38 more
  1. 2023BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Modelscited by 41
  2. 2024Seeing Motion at Nighttime with an Event Cameracited by 34
  3. 2025One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusioncited by 32
  4. 2024Text-DiFuse: An Interactive Multi-Modal Image Fusion Framework based on Text-modulated Diffusion Modelcited by 31
  5. 2023Adversarial Illusions in Multi-Modal Embeddingscited by 29
  6. 2024DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusioncited by 28
  7. 2023Unified Adversarial Patch for Cross-modal Attacks in the Physical Worldcited by 27
  8. 2024Visible-Thermal Tiny Object Detection: A Benchmark Dataset and Baselinescited by 27
  9. 2023TextFusion: Unveiling the Power of Textual Semantics for Controllable Image Fusioncited by 26
  10. 2024Task-driven Image Fusion with Learnable Fusion Losscited by 25
  11. 2023Unified Adversarial Patch for Visible-Infrared Cross-modal Attacks in the Physical Worldcited by 21
  12. 2024OmniBind: Teach to Build Unequal-Scale Modality Interaction for Omni-Bind of Allcited by 20
  13. 2025Continual Multimodal Contrastive Learningcited by 20
  14. 2022Emergent Visual Sensors for Autonomous Vehiclescited by 19
  15. 2024Caltech Aerial RGB-Thermal Dataset in the Wildcited by 19
  16. 2023TFDet: Target-Aware Fusion for RGB-T Pedestrian Detectioncited by 18
  17. 2024UniRGB-IR: A Unified Framework for Visible-Infrared Semantic Tasks via Adapter Tuningcited by 17
  18. 2024Removal then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detectioncited by 16
  19. 2025DiffV2IR: Visible-to-Infrared Diffusion Model via Vision-Language Understandingcited by 16
  20. 2024MaeFuse: Transferring Omni Features with Pretrained Masked Autoencoders for Infrared and Visible Image Fusion via Guided Trainingcited by 15
  21. 2024AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian Detectioncited by 15
  22. 2025Efficient Rectified Flow for Image Fusioncited by 15
  23. 2023MS-DETR: Multispectral Pedestrian Detection Transformer with Loosely Coupled Fusion and Modality-Balanced Optimizationcited by 14
  24. 2024All-weather Multi-Modality Image Fusion: Unified Framework and 100k Benchmarkcited by 14
  25. 2024IoT-LM: Large Multisensory Language Models for the Internet of Thingscited by 14
  26. 2025WaveMamba: Wavelet-Driven Mamba Fusion for RGB-Infrared Object Detectioncited by 14
  27. 2025ThermalGen: Style-Disentangled Flow-Based Generative Models for RGB-to-Thermal Image Translationcited by 14
  28. 2024Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detectioncited by 13
  29. 2024Visible-Thermal Multiple Object Tracking: Large-scale Video Dataset and Progressive Fusion Approachcited by 13
  30. 2024Conditional Controllable Image Fusioncited by 13
  31. 2024Leveraging Thermal Modality to Enhance Reconstruction in Low-Light Conditionscited by 12
  32. 2023FusionBooster: A Unified Image Fusion Boosting Paradigmcited by 11
  33. 2024TSJNet: A Multi-modality Target and Semantic Awareness Joint-driven Image Fusion Networkcited by 10
  34. 2024When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Datasetcited by 10
  35. 2024MMDRFuse: Distilled Mini-Model with Dynamic Refresh for Multi-Modality Image Fusioncited by 10
  36. 2024LoLI-Street: Benchmarking Low-Light Image Enhancement and Beyondcited by 10
  37. 2024Instruction-Driven Fusion of Infrared-Visible Images: Tailoring for Diverse Downstream Taskscited by 9
  38. 2025MMAIF: Multi-task and Multi-degradation All-in-One for Image Fusion with Language Guidancecited by 9

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