mlsanityData to 7 Oct 2026

OpenGlue: Open Source Graph Neural Net Based Pipeline for Image Matching

arXiv 2204.08870 ↗First posted 19 Apr 2022cs.CVcited by 3

Not on the map. Why?

Abstract (arXiv)

We present OpenGlue: a free open-source framework for image matching, that uses a Graph Neural Network-based matcher inspired by SuperGlue citesarlin20superglue. We show that including additional geometrical information, such as local feature scale, orientation, and affine geometry, when available (e.g. for SIFT features), significantly improves the performance of the OpenGlue matcher. We study the influence of the various attention mechanisms on accuracy and speed. We also present a simple architectural improvement by combining local descriptors with context-aware descriptors. The code and pretrained OpenGlue models for the different local features are publicly available.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 24 of its 47 references that are in the map. First posted on arXiv 19 Apr 2022.

Builds on

24 of 47 references.

References · 24

  1. 2017Attention Is All You Needcited by 59,932
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  4. 2017Neural Message Passing for Quantum Chemistrycited by 3,460
  5. 2013Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distancescited by 2,277
  6. 2020Transformers are RNNs: Fast Autoregressive Transformers with Linear Attentioncited by 1,979
  7. 2020Rethinking Attention with Performerscited by 1,584
  8. 2019SuperGlue: Learning Feature Matching with Graph Neural Networkscited by 1,437
  9. 2017SuperPoint: Self-Supervised Interest Point Detection and Descriptioncited by 1,313
  10. 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 983
  11. 2021LoFTR: Detector-Free Local Feature Matching with Transformerscited by 974
  12. 2015NetVLAD: CNN architecture for weakly supervised place recognitioncited by 935
12 more
  1. 2018MegaDepth: Learning Single-View Depth Prediction from Internet Photoscited by 731
  2. 2019D2-Net: A Trainable CNN for Joint Detection and Description of Local Featurescited by 324
  3. 2016Large-Scale Image Retrieval with Attentive Deep Local Featurescited by 238
  4. 2015YFCC100M: The New Data in Multimedia Researchcited by 234
  5. 2019Kornia: an Open Source Differentiable Computer Vision Library for PyTorchcited by 231
  6. 2020Image Matching across Wide Baselines: From Paper to Practicecited by 224
  7. 2017Working hard to know your neighbor's margins: Local descriptor learning losscited by 212
  8. 2019MAGSAC++, a fast, reliable and accurate robust estimatorcited by 160
  9. 2017Repeatability Is Not Enough: Learning Affine Regions via Discriminabilitycited by 57
  10. 2019Large-scale, real-time visual-inertial localization revisitedcited by 45
  11. 2017Toward Geometric Deep SLAMcited by 38
  12. 2021Learning and Crafting for the Wide Multiple Baseline Stereocited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.

3 papers.

  1. 2024Scalable Training of Trustworthy and Energy-Efficient Predictive Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNNcited by 8
  2. 2023ResMatch: Residual Attention Learning for Local Feature Matchingcited by 1
  3. 2026Understanding and Optimizing Attention-Based Sparse Matching for Diverse Local Featurescited by 0