Papers › LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
LLVIP: A Visible-infrared Paired Dataset for Low-light Vision
Xinyu Jia, Chuang Zhu, Minzhen Li, Wenqi Tang, ShengJie Liu, Wenli Zhou
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.
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Tasks
Datasets
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Image Generation | LLVIP | pix2pix | PSNR | 10.769 | #1 of 1 | Archive leaderboard | report |
| Image Generation | LLVIP | pix2pix | SSIM | 0.1757 | #1 of 1 | Archive leaderboard | report |
| Image-to-Image Translation | LLVIP | pix2pix | PSNR | 10.769 | #4 of 4 | Archive leaderboard | report |
| Image-to-Image Translation | LLVIP | pix2pix | SSIM | 0.1757 | #4 of 4 | Archive leaderboard | report |
| Pedestrian Detection | LLVIP | YoloV5-RGB | AP | 0.527 | #11 of 15 | Archive leaderboard | report |
| Pedestrian Detection | LLVIP | YoloV5-RGB | log average miss rate | 22.59% | #11 of 15 | Archive leaderboard | report |
| Pedestrian Detection | LLVIP | YoloV3-RGB | AP | 0.466 | #14 of 15 | Archive leaderboard | report |
| Pedestrian Detection | LLVIP | YoloV3-RGB | log average miss rate | 37.70% | #14 of 15 | Archive leaderboard | report |
| Thermal Infrared Pedestrian Detection | LLVIP | YoloV5 | AP | 0.670 | #1 of 2 | Archive leaderboard | report |
| Thermal Infrared Pedestrian Detection | LLVIP | YoloV3 | AP | 0.582 | #2 of 2 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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