Browse State-of-the-Art › Keypoint detection and image matching
Keypoint detection and image matching
6 papers with code · 0 benchmarks · 2 datasets archive 2025-07-28
keypoint detection in retinal images followed by image registration
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
6 shown of 6 papers with code (6 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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23 Mar 2020 4 repositories listed Syntology ran 0 of 16 samples · 16 unverifiedThis work focuses on mitigating two limitations in the joint learning of local feature detectors and descriptors.
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4 Nov 2024 1 repository listedThis paper presents a framework for extracting georeferenced vehicle trajectories from high-altitude drone footage, addressing key challenges in urban traffic monitoring and limitations of traditional ground-based…
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30 Apr 2024 1 repository listed Syntology ran 1 of 2 samples · 1 unverifiedBesides, our model is designed to offer the choice of matching at the sparse or semi-dense levels, each of which may be more suitable for different downstream applications, such as visual navigation and augmented…
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16 Feb 2024 1 repository listed Syntology ran 12 of 17 samples · 5 unverifiedGiven an architecture, GIM first trains it on standard domain-specific datasets and then combines it with complementary matching methods to create dense labels on nearby frames of novel videos.
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20 Jul 2023 1 repository listedWe propose a novel approach based on reverse knowledge distillation to train large models with limited data while preventing overfitting.
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22 Jun 2023 1 repository listedThis paper proposes a novel sparse-to-local-dense (S2LD) matching method to conduct fully differentiable correspondence estimation with the prior from epipolar geometry.
Syntology lines on 3 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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