Papers › LightGlue: Local Feature Matching at Light Speed

LightGlue: Local Feature Matching at Light Speed

23 Jun 2023ICCV 2023 1arXiv:2306.13643archive 2025-07-28

Philipp Lindenberger, Paul-Edouard Sarlin, Marc Pollefeys

We introduce LightGlue, a deep neural network that learns to match local features across images. We revisit multiple design decisions of SuperGlue, the state of the art in sparse matching, and derive simple but effective improvements. Cumulatively, they make LightGlue more efficient - in terms of both memory and computation, more accurate, and much easier to train. One key property is that LightGlue is adaptive to the difficulty of the problem: the inference is much faster on image pairs that are intuitively easy to match, for example because of a larger visual overlap or limited appearance change. This opens up exciting prospects for deploying deep matchers in latency-sensitive applications like 3D reconstruction. The code and trained models are publicly available at https://github.com/cvg/LightGlue.

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Syntology Ran 18 of 40 code samples harvested from 2 repositories linked to this paper; 22 have no recorded run. Of those that ran: 2 ran · our draft was wrong; 5 ran · fixture could not drive it; 11 ran with no contract checked.

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cvg/lightglue officialmentioned in papermentioned on GitHubpytorchApache-2.0 report
fabio-sim/LightGlue-ONNX mentioned on GitHubpytorch report

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2ran · our draft was wrong
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Tasks

3D ReconstructionCamera Pose EstimationHomography EstimationImage MatchingKey Point MatchingPose EstimationVisual Localization

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Image Matching ZEB LightGlue Mean AUC@5° 31.7 #9 of 10 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.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections