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We propose a novel framework for finding correspondences in images based on a deep neural network that, given two images and a query point in one of them, finds its correspondence in the other.
Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography
Martin A Fischler and Robert C Bolles · 1981
Earlier work this paper cites.
Determining Optical Flow
Berthold KP Horn and Brian G Schunck · 1981
Earlier work this paper cites.
An Iterative Image Registration Technique with an Application to Stereo Vision
Bruce D Lucas, Takeo Kanade, et al · 1981
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Tracking of Point Features
Carlo Tomasi and T Kanade Detection · 1991
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Multiple View Geometry in Computer Vision
Richard Hartley and Andrew Zisserman · 2003
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Distinctive Image Features from Scale-Invariant Keypoints
David G Lowe · 2004
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Distinctive image Features from Scale-Invariant Keypoints
David G Lowe · 2004
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Two-view Geometry Estimation Unaffected by a Dominant Plane
Ondrej Chum, Tomas Werner, and Jiri Matas · 2005
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Machine Learning for High-Speed Corner Detection
Edward Rosten and Tom Drummond · 2006
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Compositional Pattern Producing Networks: A Novel Abstraction of Development
Kenneth O Stanley · 2007
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Daisy: An Efficient Dense Descriptor Applied to Wide-baseline Stereo
Engin Tola, Vincent Lepetit, and Pascal Fua · 2009
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Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation
Thomas Brox and Jitendra Malik · 2010
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BRIEF: Binary Robust Independent Elementary Features
Michael Calonder, Vincent Lepetit, Christoph Strecha, and Pascal Fua · 2010
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SIFT Flow: Dense Correspondence Across Scenes and its Applications
Ce Liu, Jenny Yuen, and Antonio Torralba · 2010
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Secrets of Optical Flow Estimation and Their Principles
Deqing Sun, Stefan Roth, and Michael J Black · 2010
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Improving Image-based Localization by Active Correspondence Search
Torsten Sattler, Bastian Leibe, and Leif Kobbelt · 2012
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Vision Meets Robotics: The KITTI Dataset
Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun · 2013
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Adam: A Method for Stochastic Optimization
Diederik P Kingma and Jimmy Ba · 2014
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A Quantitative Analysis of Current Practices in Optical Flow Estimation and the Principles Behind Them
Deqing Sun, Stefan Roth, and Michael J Black · 2014
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FlowNet: Learning Optical Flow with Convolutional Networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Spatial transformer networks
Max Jaderberg, Karen Simonyan, Andrew Zisserman, and Koray Kavukcuoglu · 2015
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Joint 3D Estimation of Vehicles and Scene Flow
Moritz Menze, Christian Heipke, and Andreas Geiger · 2015
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Stacked Hourglass Networks for Human Pose estimation
Alejandro Newell, Kaiyu Yang, and Jia Deng · 2016
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Structure-from-Motion Revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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LIFT: Learned Invariant Feature Transform
Kwang Moo Yi, Eduard Trulls, Vincent Lepetit, and Pascal Fua · 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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GMS: Grid-based Motion Sstatistics 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
Cited alongside, same era.
Working Hard to Know Your Neighbor’s Margins: Local Descriptor Learning Loss
Anastasiya Mishchuk, Dmytro Mishkin, Filip Radenovic, and Jiri Matas · 2017
Cited alongside, same era.
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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On the Spectral Bias of Neural Networks
Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred Hamprecht, Yoshua Bengio, and Aaron Courville · 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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Thomas Schöps, Johannes L. Schönberger, Silvano Galliani, Torsten Sattler, Konrad Schindler, Marc Pollefeys, and Andreas Geiger · 2017
Cited alongside, same era.
Demon: Depth and Motion Network for Learning Monocular Stereo
Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig, Nikolaus Mayer, Eddy Ilg, Alexey Dosovitskiy, and Thomas Brox · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Unsupervised Learning of Depth and Ego-Motion from Video
Tinghui Zhou, Matthew Brown, Noah Snavely, and David G. Lowe · 2017
Cited alongside, same era.
SuperPoint: Self-Supervised Interest Point Detection and Description
Daniel DeTone, Tomasz Malisiewicz, and Andrew Rabinovich · 2018
Cited alongside, same era.
DensePose: Dense Human Pose Estimation In The Wild
Rıza Alp Güler, Natalia Neverova, and Iasonas Kokkinos · 2018
Cited alongside, same era.
LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation
Tak-Wai Hui, Xiaoou Tang, and Chen Change Loy · 2018
Cited alongside, same era.
Models Matter, so Does Training: An Empirical Study of CNNs for Optical Flow Estimation
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, and Jan Kautz · 2019
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SOSNet: Second Order Similarity Regularization for Local Descriptor Learning
Yurun Tian, Xin Yu, Bin Fan, Fuchao Wu, Huub Heijnen, and Vassileios Balntas · 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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SAL: Sign Agnostic Learning of Shapes from Raw Data
Matan Atzmon and Yaron Lipman · 2020
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Frequency Bias in Neural Networks for Input of Non-uniform Density
Ronen Basri, Meirav Galun, Amnon Geifman, David Jacobs, Yoni Kasten, and Shira Kritchman · 2020
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Reinforced Feature Points: Optimizing Feature Detection and Description for a High-level Task
Aritra Bhowmik, Stefan Gumhold, Carsten Rother, and Eric Brachmann · 2020
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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Handcrafted outlier detection revisited
Luca Cavalli, Viktor Larsson, Martin Ralf Oswald, Torsten Sattler, and Marc Pollefeys · 2020
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Towards Precise Completion of Deformable Shape
Oshri Halimi, Ido Imanuel, Or Litany, Giovanni Trappolini, Emanuele Rodolà, Leonidas Guibas, and Ron Kimmel · 2020
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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
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Large-scale, Real-time Visual-inertial Localization Revisited
Simon Lynen, Bernhard Zeisl, Dror Aiger, Michael Bosse, Joel Hesch, Marc Pollefeys, Roland Siegwart, and Torsten Sattler · 2020
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Improving the HardNet Descriptor
Milan Pultar · 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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ACNe: Attentive Context Normalization for Robust Permutation-Equivariant Learning
Weiwei Sun, Wei Jiang, Eduard Trulls, Andrea Tagliasacchi, and Kwang Moo Yi · 2020
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RAFT: Recurrent All-Pairs Field Transforms for Optical Flow
Zachary Teed and Jia Deng · 2020
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GLU-Net: Global-Local Universal Network for Dense Flow and Correspondences
Prune Truong, Martin Danelljan, and Radu Timofte · 2020
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GOCor: Bringing Globally Optimized Correspondence Volumes into Your Neural Network
Prune Truong, Martin Danelljan, Luc Van Gool, and Radu Timofte · 2020
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DISK: Learning Local Features with Policy Gradient
Michał J Tyszkiewicz, Pascal Fua, and Eduard Trulls · 2020
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An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, 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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