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Image matching is a fundamental computer vision problem.
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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Semi-supervised learning by entropy minimization
Yves Grandvalet and Yoshua Bengio · 2004
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Distinctive image features from scale-invariant keypoints
David G. Lowe · 2004
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Surf: Speeded up robust features
Herbert Bay, Tinne Tuytelaars, and Luc Van Gool · 2006
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Orb: An efficient alternative to sift or surf
Ethan Rublee, Vincent Rabaud, Kurt Konolige, and Gary Bradski · 2011
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Three things everyone should know to improve object retrieval
Relja Arandjelović and Andrew Zisserman · 2012
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM
A. Handa, T. Whelan, J.B. McDonald, and A.J. Davison · 2014
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Structure-from-motion revisited
Johannes L. Schönberger and Jan-Michael Frahm · 2016
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Benefit of large field-of-view cameras for visual odometry
Zichao Zhang, Henri Rebecq, Christian Forster, and Davide Scaramuzza · 2016
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Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors
Vassileios Balntas, Karel Lenc, Andrea Vedaldi, and Krystian Mikolajczyk · 2017
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Scannet: Richly-annotated 3d reconstructions of indoor scenes
Angela Dai, Angel X. Chang, Manolis Savva, Maciej Halber, Thomas A. Funkhouser, and Matthias Nießner · 2017
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1 Year, 1000km: The Oxford RobotCar Dataset
Will Maddern, Geoff Pascoe, Chris Linegar, and Paul Newman · 2017
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Scenenet rgb-d: Can 5m synthetic images beat generic imagenet pre-training on indoor segmentation?
John McCormac, Ankur Handa, Stefan Leutenegger, and Andrew J.Davison · 2017
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Working hard to know your neighbor’s margins: Local descriptor learning loss
A. Mishchuk, Dmytro Mishkin, Filip Radenović, and Jiri Matas · 2017
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A multi-view stereo benchmark with high-resolution images and multi-camera videos
Thomas Schöps, Johannes L. Schönberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger · 2017
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L2-net: Deep learning of discriminative patch descriptor in euclidean space
Yurun Tian, Bin Fan, and F. Wu · 2017
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Attention is all you need
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
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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2020
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SuperGlue: Learning feature matching with graph neural networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2020
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Disk: Learning local features with policy gradient
Michal J. Tyszkiewicz, P. Fua, and Eduard Trulls · 2020
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Flow-motion and depth network for monocular stereo and beyond
Kaixuan Wang and Shaojie Shen · 2020
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Blendedmvs: A large-scale dataset for generalized multi-view stereo networks
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Megadepth: Learning single-view depth prediction from internet photos
Zhengqi Li and Noah Snavely · 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, Fredrik Kahl, and Tomas Pajdla · 2018
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Matchable image retrieval by learning from surface reconstruction
Tianwei Shen, Zixin Luo, Lei Zhou, Runze Zhang, Siyu Zhu, Tian Fang, and Long Quan · 2018
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InLoc: Indoor visual localization with dense matching and view synthesis
Hajime Taira, Masatoshi Okutomi, Torsten Sattler, Mircea Cimpoi, Marc Pollefeys, Josef Sivic, Tomas Pajdla, and Akihiko Torii · 2018
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MAGSAC: marginalizing sample consensus
Daniel Barath, Jiri Matas, and Jana Noskova · 2019
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D2-net: A trainable cnn for joint description and detection of local features
Mihai Dusmanu, Ignacio Rocco, Tomás Pajdla, Marc Pollefeys, Josef Sivic, Akihiko Torii, and Torsten Sattler · 2019
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Yao Yao, Zixin Luo, Shiwei Li, Jingyang Zhang, Yufan Ren, Lei Zhou, Tian Fang, and Long Quan · 2020
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A survey of autonomous driving: Common practices and emerging technologies
Ekim Yurtsever, Jacob Lambert, Alexander Carballo, and Kazuya Takeda · 2020
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Loftr: Detector-free local feature matching with transformers
Jiaming Sun, Zehong Shen, Yuang Wang, Hujun Bao, and Xiaowei Zhou · 2021
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Self-supervised geometric perception
Heng Yang, Wei Dong, Luca Carlone, and Vladlen Koltun · 2021
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Dkm: Dense kernelized feature matching for geometry estimation
Johan Edstedt, Ioannis Athanasiadis, Mårten Wadenbäck, and Michael Felsberg · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Metric3d: Towards zero-shot metric 3d prediction from a single image
Wei Yin, Chi Zhang, Hao Chen, Zhipeng Cai, Gang Yu, Kaixuan Wang, Xiaozhi Chen, and Chunhua Shen · 2023
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