Fetching the paper…
Reading the bibliography…
This study addresses an image-matching problem in challenging cases, such as large scene variations or textureless scenes.
R2D2: repeatable and reliable detector and descriptor
Revaud, J.; Weinzaepfel, P.; De Souza, C.; Pion, N.; Csurka, G.; Cabon, Y.; and Humenberger, M. 2019 · 1906
Earlier work this paper cites.
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
Fischler, M. A.; and Bolles, R. C. 1981 · 1981
Earlier work this paper cites.
Latent dirichlet allocation
Blei, D. M.; Ng, A. Y.; and Jordan, M. I. 2003 · 2003
Earlier work this paper cites.
Multiple view geometry in computer vision
Hartley, R.; and Zisserman, A. 2003 · 2003
Earlier work this paper cites.
Video Google: A text retrieval approach to object matching in videos
Sivic, J.; and Zisserman, A. 2003 · 2003
Earlier work this paper cites.
Visual categorization with bags of keypoints
Csurka, G.; Dance, C.; Fan, L.; Willamowski, J.; and Bray, C. 2004 · 2004
Earlier work this paper cites.
Distinctive image features from scale-invariant keypoints
Lowe, D. G. 2004 · 2004
Earlier work this paper cites.
Robust image retrieval-based visual localization using kapture
Humenberger, M.; Cabon, Y.; Guerin, N.; Morat, J.; Revaud, J.; Rerole, P.; Pion, N.; de Souza, C.; Leroy, V.; and Csurka, G. 2020 · 2007
Earlier work this paper cites.
Speeded-up robust features (SURF)
Bay, H.; Ess, A.; Tuytelaars, T.; and Van Gool, L. 2008 · 2008
Earlier work this paper cites.
Image stylization for robust features
Melekhov, I.; Brostow, G. J.; Kannala, J.; and Turmukhambetov, D. 2020 · 2008
Earlier work this paper cites.
Detecting interpretable and accurate scale-invariant keypoints
Förstner, W.; Dickscheid, T.; and Schindler, F. 2009 · 2009
Earlier work this paper cites.
Brief: Binary robust independent elementary features
Calonder, M.; Lepetit, V.; Strecha, C.; and Fua, P. 2010 · 2010
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy, A.; Beyer, L.; Kolesnikov, A.; Weissenborn, D.; Zhai, X.; Unterthiner, T.; Dehghani, M.; Minderer, M.; Heigold, G.; Gelly, S.; et al. 2020 · 2010
Earlier work this paper cites.
ORB: An efficient alternative to SIFT or SURF
Rublee, E.; Rabaud, V.; Konolige, K.; and Bradski, G. 2011 · 2011
Earlier work this paper cites.
Improving image-based localization by active correspondence search
Sattler, T.; Leibe, B.; and Kobbelt, L. 2012 · 2012
Earlier work this paper cites.
Sinkhorn distances: Lightspeed computation of optimal transport
Cuturi, M. 2013 · 2013
Earlier work this paper cites.
A biterm topic model for short texts
Yan, X.; Guo, J.; Lan, Y.; and Cheng, X. 2013 · 2013
Earlier work this paper cites.
Microsoft coco: Common objects in context
Lin, T.-Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollár, P.; and Zitnick, C. L. 2014 · 2014
Earlier work this paper cites.
Scalable nearest neighbor algorithms for high dimensional data
Muja, M.; and Lowe, D. G. 2014 · 2014
Earlier work this paper cites.
Fully convolutional networks for semantic segmentation
Long, J.; Shelhamer, E.; and Darrell, T. 2015 · 2015
Earlier work this paper cites.
ORB-SLAM: a versatile and accurate monocular SLAM system
Mur-Artal, R.; Montiel, J. M. M.; and Tardos, J. D. 2015 · 2015
Earlier work this paper cites.
Lift: Learned invariant feature transform
Yi, K. M.; Trulls, E.; Lepetit, V.; and Fua, P. 2016 · 2016
Cited alongside, same era.
Learning deep features for discriminative localization
Zhou, B.; Khosla, A.; Lapedriza, A.; Oliva, A.; and Torralba, A. 2016 · 2016
Cited alongside, same era.
HPatches: A benchmark and evaluation of handcrafted and learned local descriptors
Balntas, V.; Lenc, K.; Vedaldi, A.; and Mikolajczyk, K. 2017 · 2017
Cited alongside, same era.
Gms: Grid-based motion statistics for fast, ultra-robust feature correspondence
Bian, J.; Lin, W.-Y.; Matsushita, Y.; Yeung, S.-K.; Nguyen, T.-D.; and Cheng, M.-M. 2017 · 2017
Cited alongside, same era.
Scannet: Richly-annotated 3d reconstructions of indoor scenes
Dai, A.; Chang, A. X.; Savva, M.; Halber, M.; Funkhouser, T.; and Nießner, M. 2017 · 2017
Cited alongside, same era.
Mask r-cnn
He, K.; Gkioxari, G.; Dollár, P.; and Girshick, R. 2017 · 2017
Efficient neighbourhood consensus networks via submanifold sparse convolutions
Rocco, I.; Arandjelović, R.; and Sivic, J. 2020 · 2020
Later among the works it cites.
Superglue: Learning feature matching with graph neural networks
Sarlin, P.-E.; DeTone, D.; Malisiewicz, T.; and Rabinovich, A. 2020 · 2020
Later among the works it cites.
DISK: Learning local features with policy gradient
Tyszkiewicz, M.; Fua, P.; and Trulls, E. 2020 · 2020
Later among the works it cites.
Explainable face recognition
Williford, J. R.; May, B. B.; and Byrne, J. 2020 · 2020
Later among the works it cites.
Object-contextual representations for semantic segmentation
Yuan, Y.; Chen, X.; and Wang, J. 2020 · 2020
Later among the works it cites.
Transformer interpretability beyond attention visualization
Chefer, H.; Gur, S.; and Wolf, L. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Grad-cam: Visual explanations from deep networks via gradient-based localization
Selvaraju, R. R.; Cogswell, M.; Das, A.; Vedantam, R.; Parikh, D.; and Batra, D. 2017 · 2017
Cited alongside, same era.
Gan dissection: Visualizing and understanding generative adversarial networks
Bau, D.; Zhu, J.-Y.; Strobelt, H.; Zhou, B.; Tenenbaum, J. B.; Freeman, W. T.; and Torralba, A. 2018 · 2018
Cited alongside, same era.
Superpoint: Self-supervised interest point detection and description
DeTone, D.; Malisiewicz, T.; and Rabinovich, A. 2018 · 2018
Cited alongside, same era.
LF-Net: Learning local features from images
Ono, Y.; Trulls, E.; Fua, P.; and Yi, K. M. 2018 · 2018
Cited alongside, same era.
Neighbourhood consensus networks
Rocco, I.; Cimpoi, M.; Arandjelović, R.; Torii, A.; Pajdla, T.; and Sivic, J. 2018 · 2018
Cited alongside, same era.
InLoc: Indoor visual localization with dense matching and view synthesis
Taira, H.; Okutomi, M.; Sattler, T.; Cimpoi, M.; Pollefeys, M.; Sivic, J.; Pajdla, T.; and Torii, A. 2018 · 2018
Cited alongside, same era.
Learning to match features with seeded graph matching network
Chen, H.; Luo, Z.; Zhang, J.; Zhou, L.; Bai, X.; Hu, Z.; Tai, C.-L.; and Quan, L. 2021 · 2021
Later among the works it cites.
Effect of Parameter Optimization on Classical and Learning-based Image Matching Methods
Efe, U.; Ince, K. G.; and Alatan, A. A. 2021 · 2021
Later among the works it cites.
Cotr: Correspondence transformer for matching across images
Jiang, W.; Trulls, E.; Hosang, J.; Tagliasacchi, A.; and Yi, K. M. 2021 · 2021
Later among the works it cites.
Image matching from handcrafted to deep features: A survey
Ma, J.; Jiang, X.; Fan, A.; Jiang, J.; and Yan, J. 2021 · 2021
Later among the works it cites.
Efficient attention: Attention with linear complexities
Shen, Z.; Zhang, M.; Zhao, H.; Yi, S.; and Li, H. 2021 · 2021
Later among the works it cites.
Segmenter: Transformer for semantic segmentation
Strudel, R.; Garcia, R.; Laptev, I.; and Schmid, C. 2021 · 2021
Later among the works it cites.
LoFTR: Detector-free local feature matching with transformers
Sun, J.; Shen, Z.; Wang, Y.; Bao, H.; and Zhou, X. 2021 · 2021
Later among the works it cites.
Interpretable image recognition by constructing transparent embedding space
Wang, J.; Liu, H.; Wang, X.; and Jing, L. 2021 · 2021
Later among the works it cites.
Reference pose generation for long-term visual localization via learned features and view synthesis
Zhang, Z.; Sattler, T.; and Scaramuzza, D. 2021 · 2021
Later among the works it cites.
Towards interpretable deep metric learning with structural matching
Zhao, W.; Rao, Y.; Wang, Z.; Lu, J.; and Zhou, J. 2021 · 2021
Later among the works it cites.
Patch2pix: Epipolar-guided pixel-level correspondences
Zhou, Q.; Sattler, T.; and Leal-Taixe, L. 2021 · 2021
Later among the works it cites.
ClusterGNN: Cluster-based Coarse-to-Fine Graph Neural Network for Efficient Feature Matching
Shi, Y.; Cai, J.-X.; Shavit, Y.; Mu, T.-J.; Feng, W.; and Zhang, K. 2022 · 2022
Closest in time.
MatchFormer: Interleaving Attention in Transformers for Feature Matching
Wang, Q.; Zhang, J.; Yang, K.; Peng, K.; and Stiefelhagen, R. 2022 · 2022
Closest in time.
Megadepth: Learning single-view depth prediction from internet photos
Li, Z.; and Snavely, N. 2018 · 2050
Closest in time.