Deep Learning Reforms Image Matching: A Survey and Outlook | Paper Citation Record

Observation 47faef8b-b794-4887-8de5-5e38ccee7647 · outbound

This paper cites Image retrieval: Ideas, influences, and trends of the new age,.

Deep Learning Reforms Image Matching: A Survey and Outlook Image retrieval: Ideas, influences, and trends of the new age,

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This paper cites Benchmarking 6dof outdoor visual localization in changing conditions,.

Deep Learning Reforms Image Matching: A Survey and Outlook Benchmarking 6dof outdoor visual localization in changing conditions,

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This paper cites Hartley and A.

Deep Learning Reforms Image Matching: A Survey and Outlook Hartley and A

Reference 3

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This paper cites Global structure-from-motion revisited,.

Deep Learning Reforms Image Matching: A Survey and Outlook Global structure-from-motion revisited,

Reference 4

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This paper cites Lsd-slam: Large-scale direct monocular slam,.

Deep Learning Reforms Image Matching: A Survey and Outlook Lsd-slam: Large-scale direct monocular slam,

Reference 5

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This paper cites 3d gaussian splatting for real-time radiance field rendering.

Deep Learning Reforms Image Matching: A Survey and Outlook 3d gaussian splatting for real-time radiance field rendering

Reference 6

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This paper cites Cooperative computation of stereo disparity: A cooperative algorithm is derived for extracting dis- parity information from stereo image pairs.

Deep Learning Reforms Image Matching: A Survey and Outlook Cooperative computation of stereo disparity: A cooperative algorithm is derived for extracting dis- parity information from stereo image pairs

Reference 7

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This paper cites Scene analysis using regions,.

Deep Learning Reforms Image Matching: A Survey and Outlook Scene analysis using regions,

Reference 8

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This paper cites Adaptive least squares correlation: a powerful image matching technique,.

Deep Learning Reforms Image Matching: A Survey and Outlook Adaptive least squares correlation: a powerful image matching technique,

Reference 9

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Observation a2590e77-e63d-49f3-96e3-36c2dd8e2bf3 · outbound

This paper cites Rover visual obstacle avoidance.

Deep Learning Reforms Image Matching: A Survey and Outlook Rover visual obstacle avoidance

Reference 10

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This paper cites Interesting interest points: A comparative study of interest point perfor- mance on a unique data set,.

Deep Learning Reforms Image Matching: A Survey and Outlook Interesting interest points: A comparative study of interest point perfor- mance on a unique data set,

Reference 11

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This paper cites Comparative evaluation of binary features,.

Deep Learning Reforms Image Matching: A Survey and Outlook Comparative evaluation of binary features,

Reference 12

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Observation 438786c9-4608-4343-9066-a9f68464f863 · outbound

This paper cites Performance compar- isons of contour-based corner detectors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Performance compar- isons of contour-based corner detectors,

Reference 13

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This paper cites Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Hpatches: A benchmark and evaluation of handcrafted and learned local descriptors,

Reference 14

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This paper cites Comparative evaluation of hand-crafted and learned local fea- tures,.

Deep Learning Reforms Image Matching: A Survey and Outlook Comparative evaluation of hand-crafted and learned local fea- tures,

Reference 15

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This paper cites Image registration methods: a survey,.

Deep Learning Reforms Image Matching: A Survey and Outlook Image registration methods: a survey,

Reference 16

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This paper cites Image matching from handcrafted to deep features: A survey,.

Deep Learning Reforms Image Matching: A Survey and Outlook Image matching from handcrafted to deep features: A survey,

Reference 17

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Observation 7f1a80b0-3a36-4574-b3ae-0508c04c4bda · outbound

This paper cites Local feature matching using deep learning: A survey,.

Deep Learning Reforms Image Matching: A Survey and Outlook Local feature matching using deep learning: A survey,

Reference 18

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This paper cites Local feature matching from detector-based to detector- free: a survey,.

Deep Learning Reforms Image Matching: A Survey and Outlook Local feature matching from detector-based to detector- free: a survey,

Reference 19

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This paper cites Learning to find good correspondences,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning to find good correspondences,

Reference 20

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This paper cites Superpoint: Self- supervised interest point detection and description,.

Deep Learning Reforms Image Matching: A Survey and Outlook Superpoint: Self- supervised interest point detection and description,

Reference 21

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This paper cites Pdc-net+: Enhanced probabilistic dense correspondence network,.

Deep Learning Reforms Image Matching: A Survey and Outlook Pdc-net+: Enhanced probabilistic dense correspondence network,

Reference 22

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This paper cites From coarse to fine: Robust hierarchical localization at large scale,.

Deep Learning Reforms Image Matching: A Survey and Outlook From coarse to fine: Robust hierarchical localization at large scale,

Reference 23

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Observation f56316af-64f1-4b76-aa7f-c229b362db62 · outbound

This paper cites Distinctive image features from scale-invariant keypoints,.

Deep Learning Reforms Image Matching: A Survey and Outlook Distinctive image features from scale-invariant keypoints,

Reference 24

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This paper cites Orb: An efficient alternative to sift or surf,.

Deep Learning Reforms Image Matching: A Survey and Outlook Orb: An efficient alternative to sift or surf,

Reference 25

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This paper cites Robust wide- baseline stereo from maximally stable extremal regions,.

Deep Learning Reforms Image Matching: A Survey and Outlook Robust wide- baseline stereo from maximally stable extremal regions,

Reference 26

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This paper cites A performance evaluation of local descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook A performance evaluation of local descriptors,

Reference 27

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Observation 0bffb3e9-2f1a-424a-8de4-80ef8b4833df · outbound

This paper cites Object recognition from local scale-invariant fea- tures,.

Deep Learning Reforms Image Matching: A Survey and Outlook Object recognition from local scale-invariant fea- tures,

Reference 28

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This paper cites A combined corner and edge detec- tor,.

Deep Learning Reforms Image Matching: A Survey and Outlook A combined corner and edge detec- tor,

Reference 29

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This paper cites Robust point matching via vector field consensus,.

Deep Learning Reforms Image Matching: A Survey and Outlook Robust point matching via vector field consensus,

Reference 30

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This paper cites Gms: Grid-based motion statistics for fast, ultra- robust feature correspondence,.

Deep Learning Reforms Image Matching: A Survey and Outlook Gms: Grid-based motion statistics for fast, ultra- robust feature correspondence,

Reference 31

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This paper cites The development and comparison of robust methods for estimating the fundamental matrix,.

Deep Learning Reforms Image Matching: A Survey and Outlook The development and comparison of robust methods for estimating the fundamental matrix,

Reference 32

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This paper cites Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,.

Deep Learning Reforms Image Matching: A Survey and Outlook Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography,

Reference 33

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This paper cites Usac: A universal framework for random sample consensus,.

Deep Learning Reforms Image Matching: A Survey and Outlook Usac: A universal framework for random sample consensus,

Reference 34

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This paper cites Magsac++, a fast, reliable and accurate robust estimator,.

Deep Learning Reforms Image Matching: A Survey and Outlook Magsac++, a fast, reliable and accurate robust estimator,

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This paper cites Fast corner detection,.

Deep Learning Reforms Image Matching: A Survey and Outlook Fast corner detection,

Reference 36

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This paper cites Learning an interest operator from human eye movements,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning an interest operator from human eye movements,

Reference 37

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This paper cites Faster and better: A machine learning approach to corner detection,.

Deep Learning Reforms Image Matching: A Survey and Outlook Faster and better: A machine learning approach to corner detection,

Reference 38

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This paper cites Predicting match- ability,.

Deep Learning Reforms Image Matching: A Survey and Outlook Predicting match- ability,

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This paper cites A survey of convo- lutional neural networks: analysis, applications, and prospects,.

Deep Learning Reforms Image Matching: A Survey and Outlook A survey of convo- lutional neural networks: analysis, applications, and prospects,

Reference 40

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This paper cites Learning convolutional filters for interest point detection,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning convolutional filters for interest point detection,

Reference 41

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This paper cites Tilde: A temporally invariant learned detector,.

Deep Learning Reforms Image Matching: A Survey and Outlook Tilde: A temporally invariant learned detector,

Reference 42

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This paper cites Toward Geometric Deep SLAM.

Deep Learning Reforms Image Matching: A Survey and Outlook Toward Geometric Deep SLAM

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This paper cites Learning covariant feature detectors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning covariant feature detectors,

Reference 44

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This paper cites Learning dis- criminative and transformation covariant local feature detectors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning dis- criminative and transformation covariant local feature detectors,

Reference 45

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This paper cites Key. net: Keypoint detection by handcrafted and learned cnn filters,.

Deep Learning Reforms Image Matching: A Survey and Outlook Key. net: Keypoint detection by handcrafted and learned cnn filters,

Reference 46

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This paper cites Key. net: Keypoint detection by handcrafted and learned cnn filters revisited,.

Deep Learning Reforms Image Matching: A Survey and Outlook Key. net: Keypoint detection by handcrafted and learned cnn filters revisited,

Reference 47

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This paper cites Ness-st: Detecting good and stable keypoints with a neural stability score and the shi- tomasi detector,.

Deep Learning Reforms Image Matching: A Survey and Outlook Ness-st: Detecting good and stable keypoints with a neural stability score and the shi- tomasi detector,

Reference 48

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This paper cites Good features to track,.

Deep Learning Reforms Image Matching: A Survey and Outlook Good features to track,

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This paper cites Self-supervised equivariant learning for oriented keypoint detection,.

Deep Learning Reforms Image Matching: A Survey and Outlook Self-supervised equivariant learning for oriented keypoint detection,

Reference 50

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This paper cites Scale-free image keypoints using differentiable persistent homology,.

Deep Learning Reforms Image Matching: A Survey and Outlook Scale-free image keypoints using differentiable persistent homology,

Reference 51

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This paper cites Pca-sift: A more distinctive representa- tion for local image descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Pca-sift: A more distinctive representa- tion for local image descriptors,

Reference 52

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This paper cites Learning linear discrimi- nant projections for dimensionality reduction of image descrip- tors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning linear discrimi- nant projections for dimensionality reduction of image descrip- tors,

Reference 53

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This paper cites Discriminative learning of local image descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Discriminative learning of local image descriptors,

Reference 54

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This paper cites Discriminant embedding for local image descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Discriminant embedding for local image descriptors,

Reference 55

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This paper cites Learning local image descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning local image descriptors,

Reference 56

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This paper cites Ldahash: Im- proved matching with smaller descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Ldahash: Im- proved matching with smaller descriptors,

Reference 57

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This paper cites Boosting binary keypoint descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Boosting binary keypoint descriptors,

Reference 58

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This paper cites Learning local feature descriptors using convex optimisation,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning local feature descriptors using convex optimisation,

Reference 59

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This paper cites Signa- ture verification using a.

Deep Learning Reforms Image Matching: A Survey and Outlook Signa- ture verification using a

Reference 60

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This paper cites Learning to compare image patches via convolutional neural networks,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning to compare image patches via convolutional neural networks,

Reference 61

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This paper cites Match- net: Unifying feature and metric learning for patch-based match- ing,.

Deep Learning Reforms Image Matching: A Survey and Outlook Match- net: Unifying feature and metric learning for patch-based match- ing,

Reference 62

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Observation bb27c1fd-6cc3-4215-b003-a6886e1950a7 · outbound

This paper cites Discriminative learning of deep convolu- tional feature point descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Discriminative learning of deep convolu- tional feature point descriptors,

Reference 63

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Observation 8b4d7e8a-16af-42cc-a6ab-783affd66b2e · outbound

This paper cites Learning spread- out local feature descriptors,.

Deep Learning Reforms Image Matching: A Survey and Outlook Learning spread- out local feature descriptors,

Reference 64

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Deep Learning Reforms Image Matching: A Survey and Outlook Learning local feature descriptors with triplets and shallow convolutional neural networks,

Reference 65

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Deep Learning Reforms Image Matching: A Survey and Outlook Learning local image de- scriptors with deep siamese and triplet convolutional networks by minimising global loss functions,

Reference 66

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Deep Learning Reforms Image Matching: A Survey and Outlook L2-net: Deep learning of discrimi- native patch descriptor in euclidean space,

Reference 67

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Deep Learning Reforms Image Matching: A Survey and Outlook Working hard to know your neighbor’s margins: Local descriptor learning loss,

Reference 68

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Deep Learning Reforms Image Matching: A Survey and Outlook Sosnet: Second order similarity regularization for local descriptor learn- ing,

Reference 69

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Deep Learning Reforms Image Matching: A Survey and Outlook Hynet: Learning local descriptor with hybrid similarity measure and triplet loss,

Reference 70

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Deep Learning Reforms Image Matching: A Survey and Outlook Local descriptors optimized for average precision,

Reference 71

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Deep Learning Reforms Image Matching: A Survey and Outlook Geodesc: Learning local descriptors by integrating geometry constraints,

Reference 72

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Deep Learning Reforms Image Matching: A Survey and Outlook Learning feature descriptors using camera pose supervision,

Reference 73

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Deep Learning Reforms Image Matching: A Survey and Outlook Steerers: A framework for rotation equivariant keypoint descriptors,

Reference 74

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Deep Learning Reforms Image Matching: A Survey and Outlook Affine steerers for structured keypoint description,

Reference 75

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Deep Learning Reforms Image Matching: A Survey and Outlook Contextdesc: Local descriptor augmentation with cross-modality context,

Reference 76

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Deep Learning Reforms Image Matching: A Survey and Outlook Repeatability is not enough: Learning affine regions via discriminability,

Reference 77

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Deep Learning Reforms Image Matching: A Survey and Outlook Beyond cartesian representations for local descriptors,

Reference 78

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Deep Learning Reforms Image Matching: A Survey and Outlook Gift: Learning transformation-invariant dense visual descriptors via group cnns,

Reference 79

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Deep Learning Reforms Image Matching: A Survey and Outlook Group equivariant convolutional networks,

Reference 80

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Deep Learning Reforms Image Matching: A Survey and Outlook Learning rotation- equivariant features for visual correspondence,

Reference 81

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Deep Learning Reforms Image Matching: A Survey and Outlook General e (2)-equivariant steerable cnns,

Reference 82

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Deep Learning Reforms Image Matching: A Survey and Outlook Online invariance selection for local feature descriptors,

Reference 83

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Deep Learning Reforms Image Matching: A Survey and Outlook Lift: Learned invariant feature transform,

Reference 84

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Deep Learning Reforms Image Matching: A Survey and Outlook Lf-net: Learning local features from images,

Reference 85

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Deep Learning Reforms Image Matching: A Survey and Outlook Spatial trans- former networks,

Reference 86

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Deep Learning Reforms Image Matching: A Survey and Outlook Rf-net: An end-to-end image matching network based on receptive field,

Reference 87

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Deep Learning Reforms Image Matching: A Survey and Outlook Alike: Accurate and lightweight keypoint detection and descriptor ex- traction,

Reference 88

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Deep Learning Reforms Image Matching: A Survey and Outlook Aliked: A lighter keypoint and descriptor extraction network via de- formable transformation,

Reference 89

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Deep Learning Reforms Image Matching: A Survey and Outlook D2-net: A trainable cnn for joint description and detection of local features,

Reference 90

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Deep Learning Reforms Image Matching: A Survey and Outlook Aslfeat: Learning local features of accurate shape and localization,

Reference 91

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Deep Learning Reforms Image Matching: A Survey and Outlook Deformable convolutional networks,

Reference 92

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Deep Learning Reforms Image Matching: A Survey and Outlook Redfeat: Recoupling detection and descrip- tion for multimodal feature learning,

Reference 93

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Deep Learning Reforms Image Matching: A Survey and Outlook Disk: Learning local features with policy gradient,

Reference 94

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Deep Learning Reforms Image Matching: A Survey and Outlook Unresolved cited work

Reference 95

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Deep Learning Reforms Image Matching: A Survey and Outlook R2d2: Reliable and repeatable detector and descriptor,

Reference 96

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Deep Learning Reforms Image Matching: A Survey and Outlook Sfd2: Semantic-guided fea- ture detection and description,

Reference 97

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Deep Learning Reforms Image Matching: A Survey and Outlook Dedode: Detect, don’t describe—describe, don’t detect for local feature matching,

Reference 98

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Deep Learning Reforms Image Matching: A Survey and Outlook Dedode v2: Analyzing and improving the dedode keypoint detector,

Reference 99

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Deep Learning Reforms Image Matching: A Survey and Outlook Xfeat: Accelerated features for lightweight image matching,

Reference 100

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