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Local feature matching is a critical component of many computer vision pipelines, including among others Structure-from-Motion, SLAM, and Visual Localization.
The interpretation of structure from motion
Shimon Ullman · 1979
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Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Martin A Fischler and Robert C Bolles · 1981
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A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry
Zhengyou Zhang, Rachid Deriche, Olivier Faugeras, and Quang-Tuan Luong · 1995
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Triangulation
Richard I Hartley and Peter Sturm · 1997
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Mlesac: A new robust estimator with application to estimating image geometry
Philip HS Torr and Andrew Zisserman · 2000
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A robust interest points matching algorithm
Il-Kyun Jung and Simon Lacroix · 2001
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Fastslam: A factored solution to the simultaneous localization and mapping problem
Michael Montemerlo, Sebastian Thrun, Daphne Koller, Ben Wegbreit, et al · 2002
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Napsac: High noise, high dimensional robust estimation-it’s in the bag
Philip Hilaire Torr, Slawomir J Nasuto, and John Mark Bishop · 2002
Earlier work this paper cites.
Locally optimized ransac
Ondřej Chum, Jiří Matas, and Josef Kittler · 2003
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Distinctive image features from scale-invariant keypoints
David G Lowe · 2004
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A probabilistic criterion to detect rigid point matches between two images and estimate the fundamental matrix
Lionel Moisan and Bérenger Stival · 2004
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Matching with prosac-progressive sample consensus
Ondrej Chum and Jiri Matas · 2005
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Amlesac: A new maximum likelihood robust estimator
Anton Konouchine, Victor Gaganov, and Vladimir Veznevets · 2005
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A spectral technique for correspondence problems using pairwise constraints
Marius Leordeanu and Martial Hebert · 2005
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Simultaneous localization and mapping (slam): Part ii
Tim Bailey and Hugh Durrant-Whyte · 2006
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Simultaneous localization and mapping: part i
Hugh Durrant-Whyte and Tim Bailey · 2006
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Ransac for (quasi-) degenerate data (qdegsac)
J-M Frahm and Marc Pollefeys · 2006
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Optimal randomized ransac
Ondřej Chum and Jiří Matas · 2008
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Hamming embedding and weak geometric consistency for large scale image search
Herve Jegou, Matthijs Douze, and Cordelia Schmid · 2008
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Efficient visual search of videos cast as text retrieval
Josef Sivic and Andrew Zisserman · 2008
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On benchmarking camera calibration and multi-view stereo for high resolution imagery
Christoph Strecha, Wolfgang Von Hansen, Luc Van Gool, Pascal Fua, and Ulrich Thoennessen · 2008
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Geometric estimation with local affine frames and free-form surfaces
Kevin Köser · 2009
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Groupsac: Efficient consensus in the presence of groupings
Kai Ni, Hailin Jin, and Frank Dellaert · 2009
Earlier work this paper cites.
Scramsac: Improving ransac’s efficiency with a spatial consistency filter
Torsten Sattler, Bastian Leibe, and Leif Kobbelt · 2009
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Bundling features for large scale partial-duplicate web image search
Zhong Wu, Qifa Ke, Michael Isard, and Jian Sun · 2009
Cited alongside, same era.
Robust game-theoretic inlier selection for bundle adjustment
Andrea Albarelli, Emanuele Rodola, and Andrea Torsello · 2010
Cited alongside, same era.
Efficient sequential correspondence selection by cosegmentation
Jan Cech, Jiri Matas, and Michal Perdoch · 2010
Cited alongside, same era.
Location recognition using prioritized feature matching
Yunpeng Li, Noah Snavely, and Daniel P Huttenlocher · 2010
Cited alongside, same era.
Orb: An efficient alternative to sift or surf
Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski · 2011
Cited alongside, same era.
Siftgpu: A gpu implementation of scale invariant feature transform (sift)
Changchang Wu · 2011
Cited alongside, same era.
Pixelwise view selection for unstructured multi-view stereo
Johannes Lutz Schönberger, Enliang Zheng, Marc Pollefeys, and Jan-Michael Frahm · 2016
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Yfcc100m: The new data in multimedia research
Bart Thomee, David A Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Li-Jia Li · 2016
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Gms: Grid-based motion statistics for fast, ultra-robust feature correspondence
JiaWang Bian, Wen-Yan Lin, Yasuyuki Matsushita, Sai-Kit Yeung, Tan-Dat Nguyen, and Ming-Ming Cheng · 2017
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Code: Coherence based decision boundaries for feature correspondence
Wen-Yan Lin, Fan Wang, Ming-Ming Cheng, Sai-Kit Yeung, Philip HS Torr, Minh N Do, and Jiangbo Lu · 2017
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Working hard to know your neighbor’s margins: Local descriptor learning loss
Anastasiia Mishchuk, Dmytro Mishkin, Filip Radenovic, and Jiri Matas · 2017
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Multicore bundle adjustment
Changchang Wu, Sameer Agarwal, Brian Curless, and Steven M Seitz · 2011
Cited alongside, same era.
Visualsfm: A visual structure from motion system, 2011
Changchang Wu et al · 2011
Cited alongside, same era.
Fixing the locally optimized ransac–full experimental evaluation
Karel Lebeda, Jirı Matas, and Ondrej Chum · 2012
Cited alongside, same era.
Adaptive structure from motion with a contrario model estimation
Pierre Moulon, Pascal Monasse, and Renaud Marlet · 2012
Cited alongside, same era.
Usac: a universal framework for random sample consensus
Rahul Raguram, Ondrej Chum, Marc Pollefeys, Jiri Matas, and Jan-Michael Frahm · 2012
Cited alongside, same era.
Image retrieval for image-based localization revisited
Torsten Sattler, Tobias Weyand, Bastian Leibe, and Leif Kobbelt · 2012
Cited alongside, same era.
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Graph-cut ransac
Daniel Barath and Jiří Matas · 2018
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Eigendecomposition-free training of deep networks with zero eigenvalue-based losses
Zheng Dang, Kwang Moo Yi, Yinlin Hu, Fei Wang, Pascal Fua, and Mathieu Salzmann · 2018
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Learning to find good correspondences
Kwang Moo Yi, Eduard Trulls, Yuki Ono, Vincent Lepetit, Mathieu Salzmann, and Pascal Fua · 2018
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Deep fundamental matrix estimation
René Ranftl and Vladlen Koltun · 2018
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Neighbourhood consensus networks
Ignacio Rocco, Mircea Cimpoi, Relja Arandjelović, Akihiko Torii, Tomas Pajdla, and Josef Sivic · 2018
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Benchmarking 6dof outdoor visual localization in changing conditions
Torsten Sattler, Will Maddern, Carl Toft, Akihiko Torii, Lars Hammarstrand, Erik Stenborg, Daniel Safari, Masatoshi Okutomi, Marc Pollefeys, Josef Sivic, et al · 2018
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Magsac: marginalizing sample consensus
Daniel Barath, Jiri Matas, and Jana Noskova · 2019
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Neural-guided ransac: Learning where to sample model hypotheses
Eric Brachmann and Carsten Rother · 2019
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D2-net: A trainable cnn for joint description and detection of local features
Mihai Dusmanu, Ignacio Rocco, Tomas Pajdla, Marc Pollefeys, Josef Sivic, Akihiko Torii, and Torsten Sattler · 2019
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Contextdesc: Local descriptor augmentation with cross-modality context
Zixin Luo, Tianwei Shen, Lei Zhou, Jiahui Zhang, Yao Yao, Shiwei Li, Tian Fang, and Long Quan · 2019
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Locality preserving matching
Jiayi Ma, Ji Zhao, Junjun Jiang, Huabing Zhou, and Xiaojie Guo · 2019
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R2d2: Repeatable and reliable detector and descriptor
Jerome Revaud, Philippe Weinzaepfel, César De Souza, Noe Pion, Gabriela Csurka, Yohann Cabon, and Martin Humenberger · 2019
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From coarse to fine: Robust hierarchical localization at large scale
Paul-Edouard Sarlin, Cesar Cadena, Roland Siegwart, and Marcin Dymczyk · 2019
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Superglue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2019
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Learning two-view correspondences and geometry using order-aware network
Jiahui Zhang, Dawei Sun, Zixin Luo, Anbang Yao, Lei Zhou, Tianwei Shen, Yurong Chen, Long Quan, and Hongen Liao · 2019
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Nm-net: Mining reliable neighbors for robust feature correspondences
Chen Zhao, Zhiguo Cao, Chi Li, Xin Li, and Jiaqi Yang · 2019
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Image matching across wide baselines: From paper to practice
Yuhe Jin, Dmytro Mishkin, Anastasiia Mishchuk, Jiri Matas, Pascal Fua, Kwang Moo Yi, and Eduard Trulls · 2020
Closest in time.
Tsun-Yi Yang, Duy-Kien Nguyen, Huub Heijnen, and Vassileios Balntas · 2020
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