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

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. 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.

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• 1 In this case, infrared and visible images can be used together to provide both rich detail information and effective target areas.
• 2 In this paper, we present LLVIP, a visible-infrared paired dataset for low-light vision.
• 3 This dataset contains 33672 images, or 16836 pairs, most of which were taken at very dark scenes, and all of the images are strictly aligned in time and space.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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