7.1.8.2 Keypoint Detection

Chapter Contents (Back)
Interest Points. Key Points. Keypoints. More general:
See also Interest Operators, Interest Points, Feature Points, Salient Points.

Lepetit, V.[Vincent], Fua, P.[Pascal],
Keypoint Recognition Using Randomized Trees,
PAMI(28), No. 9, September 2006, pp. 1465-1479.
IEEE DOI 0608
BibRef

Ozuysal, M.[Mustafa], Calonder, M.[Michael], Lepetit, V.[Vincent], Fua, P.[Pascal],
Fast Keypoint Recognition Using Random Ferns,
PAMI(32), No. 3, March 2010, pp. 448-461.
IEEE DOI 1002
BibRef
Earlier: A2, A3, A4, Only:
Keypoint Signatures for Fast Learning and Recognition,
ECCV08(I: 58-71).
Springer DOI 0810
BibRef
Earlier: A1, A4, A3, Only:
Fast Keypoint Recognition in Ten Lines of Code,
CVPR07(1-8).
IEEE DOI 0706
Feature point recognition for object detection. Patches around key points. BibRef

Calonder, M.[Michael], Lepetit, V.[Vincent], Ozuysal, M.[Mustafa], Trzcinski, T.[Tomasz], Strecha, C.[Christoph], Fua, P.[Pascal],
BRIEF: Computing a Local Binary Descriptor Very Fast,
PAMI(34), No. 7, July 2012, pp. 1281-1298.
IEEE DOI 1205
BibRef
Earlier: A1, A2, A5, A6, Only:
BRIEF: Binary Robust Independent Elementary Features,
ECCV10(IV: 778-792).
Springer DOI Award, Koenderink Prize. 1009
Binary descriptor to compare feature poitns. SIFT started it. Directly compute the binary value (not floating point values), much faster than SIFT and SURF. BibRef

Trzcinski, T.[Tomasz], Christoudias, M.[Mario], Lepetit, V.[Vincent],
Learning Image Descriptors with Boosting,
PAMI(37), No. 3, March 2015, pp. 597-610.
IEEE DOI 1502
Boosting BibRef

Trzcinski, T.[Tomasz], Christoudias, M.[Mario], Fua, P.[Pascal], Lepetit, V.[Vincent],
Boosting Binary Keypoint Descriptors,
CVPR13(2874-2881)
IEEE DOI 1309
Binary Embedding; Binary Local Feature Descriptors; Boosting BibRef

Trzcinski, T.[Tomasz], Lepetit, V.[Vincent],
Efficient Discriminative Projections for Compact Binary Descriptors,
ECCV12(I: 228-242).
Springer DOI 1210
BibRef

Calonder, M.[Michael], Lepetit, V.[Vincent], Fua, P.[Pascal],
Pareto-optimal dictionaries for signatures,
CVPR10(3011-3018).
IEEE DOI 1006
image patch descriptors. BibRef

Lepetit, V.[Vincent], Lagger, P.[Pascal], Fua, P.[Pascal],
Randomized Trees for Real-Time Keypoint Recognition,
CVPR05(II: 775-781).
IEEE DOI 0507
Wide baseline matching as a classification problem. BibRef

Ozuysal, M.[Mustafa], Lepetit, V.[Vincent], Fua, P.[Pascal],
Pose estimation for category specific multiview object localization,
CVPR09(778-785).
IEEE DOI 0906
BibRef

Serradell, E.[Eduard], Özuysal, M.[Mustafa], Lepetit, V.[Vincent], Fua, P.[Pascal], Moreno-Noguer, F.[Francesc],
Combining Geometric and Appearance Priors for Robust Homography Estimation,
ECCV10(III: 58-72).
Springer DOI 1009
BibRef

Moreno-Noguer, F.[Francesc], Lepetit, V.[Vincent], Fua, P.[Pascal],
Pose Priors for Simultaneously Solving Alignment and Correspondence,
ECCV08(II: 405-418).
Springer DOI 0810
BibRef

Lepetit, V., Pilet, J., Fua, P.,
Point matching as a classification problem for fast and robust object pose estimation,
CVPR04(II: 244-250).
IEEE DOI 0408
BibRef

Tola, E.[Engin], Lepetit, V.[Vincent], Fua, P.[Pascal],
DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo,
PAMI(32), No. 5, May 2010, pp. 815-830.
IEEE DOI 1003
BibRef
Earlier:
A fast local descriptor for dense matching,
CVPR08(1-8).
IEEE DOI 0806
Dense local descriptor used for dense stereo matching. More robust than correlation. BibRef

Calonder, M.[Michael], Lepetit, V.[Vincent], Fua, P.[Pascal], Konolige, K.G.[Kurt G.], Bowman, J.[James], Mihelich, P.[Patrick],
Compact signatures for high-speed interest point description and matching,
ICCV09(357-364).
IEEE DOI 0909
BibRef

Li, J.[Jing], Yang, T.[Tao], Pan, Q.[Quan], Cheng, Y.M.[Yong-Mei], Hou, J.[Jun],
A Novel Algorithm For Speeding Up Keypoint Detection And Matching,
IJIG(8), No. 4, October 2008, pp. 643-661. 0804
BibRef

Mishra, A.K.[Akshaya K.], Wong, A.[Alexander], Clausi, D.A.[David A.], Fieguth, P.W.[Paul W.],
Quasi-random nonlinear scale space,
PRL(31), No. 13, 1 October 2010, pp. 1850-1859.
Elsevier DOI 1003
BibRef
Earlier: A2, A1, A3, A4:
Quasi-Random Scale Space Approach to Robust Keypoint Extraction in High-Noise Environments,
CRV10(25-31).
IEEE DOI 1005
Nonlinear scale space; Bayesian estimation; Quasi-random; Anisotropic diffusion; Multi-scale; Edge detection BibRef

Mishra, A.K.[Akshaya K.], Wong, A.[Alexander], Fieguth, P.W.[Paul W.], Clausi, D.A.[David A.],
Multi-scale 3D representation via volumetric quasi-random scale space,
ICIP11(2105-2108).
IEEE DOI 1201
BibRef

Park, U., Park, J., Jain, A.K.,
Robust Keypoint Detection Using Higher-Order Scale Space Derivatives: Application to Image Retrieval,
SPLetters(21), No. 8, August 2014, pp. 962-965.
IEEE DOI 1406
Accuracy BibRef

Tian, T., Sethi, I., Ming, D., Patel, N.,
A Zoned Image Patch Permutation Descriptor,
SPLetters(22), No. 6, June 2015, pp. 728-732.
IEEE DOI 1411
oFAST for keypoints with orientations, then patterns applied within the local keypoint patch. BibRef

Yu, X., Yang, J., Wang, T., Huang, T.,
Key Point Detection by Max Pooling for Tracking,
Cyber(45), No. 3, March 2015, pp. 444-452.
IEEE DOI 1502
Cybernetics BibRef

Yu, X., Yang, J., Lin, Z., Wang, J., Wang, T., Huang, T.,
Subcategory-Aware Object Detection,
SPLetters(22), No. 9, September 2015, pp. 1472-1476.
IEEE DOI 1503
Clustering algorithms BibRef

Buoncompagni, S.[Simone], Maio, D.[Dario], Maltoni, D.[Davide], Papi, S.[Serena],
Saliency-based keypoint selection for fast object detection and matching,
PRL(62), No. 1, 2015, pp. 32-40.
Elsevier DOI 1507
Feature selection BibRef

Zhu, J.K.[Jian-Ke], Wu, C.X.[Chen-Xia], Chen, C.[Chun], Cai, D.[Deng],
Treelets Binary Feature Retrieval for Fast Keypoint Recognition,
Cyber(45), No. 10, October 2015, pp. 2129-2141.
IEEE DOI 1509
Computed tomography BibRef

Wu, C.X.[Chen-Xia], Zhu, J.K.[Jian-Ke], Zhang, J.[Jiemi], Chen, C.[Chun], Cai, D.[Deng],
A Convolutional Treelets Binary Feature Approach to Fast Keypoint Recognition,
ECCV12(V: 368-382).
Springer DOI 1210
BibRef

Theodosiou, Z.[Zenonas],
Image Retrieval: Modelling Keywords via Low-level Features,
ELCVIA(14), No. 3, 2015, pp. xx-yy.
DOI Link 1601
Thesis summary. BibRef

Theodosiou, Z., Tsapatsoulis, N.,
Spatial histogram of keypoints (SHIK),
ICIP13(2924-2928)
IEEE DOI 1402
Hilbert space-filling curve BibRef

Tsai, C.Y., Huang, C.H., Tsao, A.H.,
Graphics processing unit-accelerated multi-resolution exhaustive search algorithm for real-time keypoint descriptor matching in high-dimensional spaces,
IET-CV(10), No. 3, 2016, pp. 212-219.
DOI Link 1604
feature extraction. GPU implementation. BibRef

Karpushin, M.[Maxim], Valenzise, G.[Giuseppe], Dufaux, F.[Frederic],
Keypoint Detection in RGBD Images Based on an Anisotropic Scale Space,
MultMed(18), No. 9, September 2016, pp. 1762-1771.
IEEE DOI 1609
BibRef
Earlier:
Improving distinctiveness of BRISK features using depth maps,
ICIP15(2399-2403)
IEEE DOI 1512
feature extraction. BRISK; RGBD features; binary descriptor; distinctiveness; texture+depth BibRef

Rey-Otero, I.[Ives], Morel, J.M.[Jean-Michel], Delbracio, M.[Mauricio],
An Analysis of the Factors Affecting Keypoint Stability in Scale-Space,
JMIV(56), No. 3, November 2016, pp. 554-572.
Springer DOI 1609
BibRef

Lomeli-Rodriguez, J.[Jaime], Nixon, M.S.[Mark S.],
An extension to the brightness clustering transform and locally contrasting keypoints,
MVA(27), No. 8, November 2016, pp. 1187-1196.
Springer DOI 1612
BibRef
Earlier:
The Brightness Clustering Transformand Locally Contrasting Keypoints,
CAIP15(I:362-373).
Springer DOI 1511
BibRef

Royer, E.[Emilien], Lelore, T.[Thibault], Bouchara, F.[Frédéric],
COnfusion REduction (CORE) algorithm for local descriptors, floating-point and binary cases,
CVIU(158), No. 1, 2017, pp. 115-125.
Elsevier DOI 1704
Keypoints filtering BibRef

Matusiak, K.[Karol], Skulimowski, P.[Piotr], Strumillo, P.[Pawel],
Unbiased evaluation of keypoint detectors with respect to rotation invariance,
IET-CV(11), No. 7, October 2017, pp. 507-516.
DOI Link 1709
BibRef

Chatoux, H.[Hermine], Richard, N.[Noël], Lecellier, F.[François], Fernandez-Maloigne, C.[Christine],
Full-Vector Gradient for Multi-Spectral or Multivariate Images,
IP(28), No. 5, May 2019, pp. 2228-2241.
IEEE DOI 1903
feature extraction, gradient methods, image colour analysis, matrix algebra, full-vector gradient, gradient extraction, color BibRef

Chatoux, H.[Hermine], Lecellier, F.[François], Fernandez-Maloigne, C.[Christine],
Comparative study of descriptors with dense key points,
ICPR16(1988-1993)
IEEE DOI 1705
Detectors, Histograms, Latches, Lighting, Protocols, Retina, Shearing BibRef

Hong-Phuoc, T.[Thanh], Guan, L.[Ling],
A Novel Key-Point Detector Based on Sparse Coding,
IP(29), No. 1, 2020, pp. 747-756.
IEEE DOI 1910
Detectors, Lighting, Image coding, Dictionaries, Complexity theory, Measurement, Training, Key-point, interest point, feature detector, sparse coding BibRef

Guan, T.H.P.<.[Thanh Hong-Phuoc/A1>, Ling],
A Novel Learning Dictionary for Sparse Coding-Based Key Point Detection,
MultMedMag(30), No. 4, October 2023, pp. 47-60.
IEEE DOI 2401
BibRef

Hong-Phuoc, T.[Thanh], He, Y.F.[Yi-Feng], Guan, L.[Ling],
SCK: A Sparse Coding Based Key-Point Detector,
ICIP18(3768-3772)
IEEE DOI 1809
Detectors, Encoding, Feature extraction, Complexity theory, Periodic structures, Measurement, Dictionaries, Key-point, sparse representation BibRef

Wang, S.[Song], Guo, X.[Xin], Tie, Y.[Yun], Qi, L.[Lin], Guan, L.[Ling],
Deep Local Feature Descriptor Learning With Dual Hard Batch Construction,
IP(29), 2020, pp. 9572-9583.
IEEE DOI 2011
BibRef
And:
Local Feature Descriptors with Deep Hypersphere Learning,
ICIP21(1524-1528)
IEEE DOI 2201
Training, Strain, Task analysis, Measurement, Deep learning, Computer architecture, Benchmark testing, triplet loss function. Benchmark testing, Feature extraction, Standards, Descriptor Learning, Hyperspherical Space BibRef

Xu, J.[Jie], Zhao, L.[Lin], Zhang, S.S.[Shan-Shan], Gong, C.[Chen], Yang, J.[Jian],
Multi-task learning for object keypoints detection and classification,
PRL(130), 2020, pp. 182-188.
Elsevier DOI 2002
Object keypoints detection, Classification, Multi-task learning BibRef

Mukherjee, S., Lagache, T., Olivo-Marin, J.C.,
Evaluating the Stability of Spatial Keypoints via Cluster Core Correspondence Index,
IP(30), 2021, pp. 386-401.
IEEE DOI 2012
Detectors, Stability criteria, Indexes, Feature extraction, Task analysis, Estimation, benchmarking BibRef

Xu, J.J.[Jun-Jie], Song, B.[Bin], Yang, X.[Xi], Nan, X.T.[Xiao-Ting],
An Improved Deep Keypoint Detection Network for Space Targets Pose Estimation,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Mousavi, V.[Vahid], Varshosaz, M.[Masood], Remondino, F.[Fabio],
Using Information Content to Select Keypoints for UAV Image Matching,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Shen, X.L.[Xue-Lun], Wang, C.[Cheng], Li, X.[Xin], Peng, Y.F.[Yi-Fan], He, Z.J.[Zi-Jian], Wen, C.L.[Cheng-Lu], Cheng, M.[Ming],
Learning scale awareness in keypoint extraction and description,
PR(121), 2022, pp. 108221.
Elsevier DOI 2109
Keypoint detection, Keypoint description, Image matching, Structure from motion, 3D reconstruction BibRef

Cho, E.[Eunhee], Kim, Y.[Yoonjin],
Dynamic Optimization of Hessian Determinant Image Pyramid for Memory-Efficient and High Performance Keypoint Detection in SURF,
IET-IPR(15), No. 13, 2021, pp. 3392-3399.
DOI Link 2110
BibRef

Leng, J.[Jiaxu], Liu, Y.[Ying], Wang, Z.H.[Zhi-Hui], Hu, H.B.[Hai-Bo], Gao, X.B.[Xin-Bo],
CrossNet: Detecting Objects as Crosses,
MultMed(24), 2022, pp. 861-875.
IEEE DOI 2202
Deep learning, Costs, Convolution, Estimation, Object detection, Prediction methods, Detectors, Keypoint localization, size regression BibRef

Zheng, Q.[Qi], Gong, M.M.[Ming-Ming], You, X.G.[Xin-Ge], Tao, D.C.[Da-Cheng],
A Unified B-Spline Framework for Scale-Invariant Keypoint Detection,
IJCV(130), No. 3, March 2022, pp. 777-799.
Springer DOI 2203
BibRef

Zhao, X.M.[Xiao-Ming], Liu, J.M.[Jing-Meng], Wu, X.M.[Xing-Ming], Chen, W.H.[Wei-Hai], Guo, F.H.[Fang-Hong], Li, Z.G.[Zheng-Guo],
Probabilistic Spatial Distribution Prior Based Attentional Keypoints Matching Network,
CirSysVideo(32), No. 3, March 2022, pp. 1313-1327.
IEEE DOI 2203
Graphical models, Distribution functions, Feature extraction, Probabilistic logic, Simultaneous localization and mapping, sensor fusion BibRef

Barroso-Laguna, A.[Axel], Mikolajczyk, K.[Krystian],
Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters Revisited,
PAMI(45), No. 1, January 2023, pp. 698-711.
IEEE DOI 2212
Detectors, Feature extraction, Computer architecture, Feature detection, Estimation, Training, Local features, 3D reconstruction BibRef

Barroso-Laguna, A.[Axel], Riba, E., Ponsa, D., Mikolajczyk, K.[Krystian],
Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters,
ICCV19(5835-5843)
IEEE DOI 2004
convolutional neural nets, feature extraction, image filtering, image matching, image representation, BibRef

Zhong, X.[Xian], Wang, M.[Mengdie], Liu, W.X.[Wen-Xuan], Yuan, J.L.[Jing-Ling], Huang, W.X.[Wen-Xin],
SCPNet: Self-constrained parallelism network for keypoint-based lightweight object detection,
JVCIR(90), 2023, pp. 103719.
Elsevier DOI 2301
Keypoint-based lightweight object detection, Parallel multi-scale fusion, Parallel shuffle block, Self-constrained detection BibRef

Zhang, Y.J.[Yun-Jian], Liu, Y.W.[Yan-Wei], Liu, J.X.[Jin-Xia], Argyriou, A.[Antonios], Wang, L.M.[Li-Ming], Xu, Z.[Zhen], Ji, X.Y.[Xiang-Yang],
Perspectively Equivariant Keypoint Learning for Omnidirectional Images,
IP(32), 2023, pp. 2552-2567.
IEEE DOI 2305
Feature extraction, Detectors, Kernel, Training, Convolution, Deformation, Task analysis, Omnidirectional images, perspectively equivariant keypoint BibRef

Mallis, D.[Dimitrios], Sanchez, E.[Enrique], Bell, M.[Matt], Tzimiropoulos, G.[Georgios],
From Keypoints to Object Landmarks via Self-Training Correspondence: A Novel Approach to Unsupervised Landmark Discovery,
PAMI(45), No. 7, July 2023, pp. 8390-8404.
IEEE DOI 2306
Detectors, Task analysis, Strain, Semantics, Faces, Unsupervised learning, Training, Unsupervised landmark discovery, keypoints BibRef

Zhao, X.M.[Xiao-Ming], Wu, X.M.[Xing-Ming], Miao, J.[Jinyu], Chen, W.H.[Wei-Hai], Chen, P.C.Y.[Peter C. Y.], Li, Z.G.[Zheng-Guo],
ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor Extraction,
MultMed(25), 2023, pp. 3101-3112.
IEEE DOI 2309
BibRef

Cadar, F.[Felipe], Melo, W.[Welerson], Kanagasabapathi, V.[Vaishnavi], Potje, G.[Guilherme], Martins, R.[Renato], Nascimento, E.R.[Erickson R.],
Improving the matching of deformable objects by learning to detect keypoints,
PRL(175), 2023, pp. 83-89.
Elsevier DOI Code:
WWW Link. 2311
Detector, Local features, Non-rigid deformations, Image matching BibRef

Gao, Y.[Yuan], He, J.F.[Jian-Feng], Zhang, T.Z.[Tian-Zhu], Zhang, Z.[Zhe], Zhang, Y.D.[Yong-Dong],
Dynamic Keypoint Detection Network for Image Matching,
PAMI(45), No. 12, December 2023, pp. 14404-14419.
IEEE DOI 2311
BibRef

Xu, R.T.[Rong-Tao], Wang, C.W.[Chang-Wei], Xu, S.B.[Shi-Biao], Meng, W.L.[Wei-Liang], Zhang, Y.Y.[Yu-Yang], Fan, B.[Bin], Zhang, X.P.[Xiao-Peng],
DomainFeat: Learning Local Features With Domain Adaptation,
CirSysVideo(34), No. 1, January 2024, pp. 46-59.
IEEE DOI 2401
BibRef

Ding, Y.[Yuhe], Liang, J.[Jian], Jiang, B.[Bo], Zheng, A.[Aihua], He, R.[Ran],
MAPS: A Noise-Robust Progressive Learning Approach for Source-Free Domain Adaptive Keypoint Detection,
CirSysVideo(34), No. 3, March 2024, pp. 1376-1387.
IEEE DOI Code:
WWW Link. 2403
Task analysis, Training, Adaptation models, Data models, Noise measurement, Animals, Predictive models, noise-robust learning BibRef


Zhong, C.L.[Cheng-Liang], Zheng, Y.H.[Yu-Hang], Zheng, Y.P.[Yu-Peng], Zhao, H.[Hao], Yi, L.[Li], Mu, X.D.[Xiao-Dong], Wang, L.[Ling], Li, P.F.[Peng-Fei], Zhou, G.[Guyue], Yang, C.[Chao], Zhang, X.L.[Xin-Liang], Zhao, J.[Jian],
3D Implicit Transporter for Temporally Consistent Keypoint Discovery,
ICCV23(3846-3857)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yang, J.[Jie], Zeng, A.[Ailing], Li, F.[Feng], Liu, S.[Shilong], Zhang, R.[Ruimao], Zhang, L.[Lei],
Neural Interactive Keypoint Detection,
ICCV23(15076-15086)
IEEE DOI 2401
BibRef

Gleize, P.[Pierre], Wang, W.Y.[Wei-Yao], Feiszli, M.[Matt],
SiLK: Simple Learned Keypoints,
ICCV23(22442-22451)
IEEE DOI 2401
BibRef

Zohaib, M.[Mohammad], del Bue, A.[Alessio],
SC3K: Self-supervised and Coherent 3D Keypoints Estimation from Rotated, Noisy, and Decimated Point Cloud Data,
ICCV23(22452-22462)
IEEE DOI Code:
WWW Link. 2401
BibRef

Pakulev, K.[Konstantin], Vakhitov, A.[Alexander], Ferrer, G.[Gonzalo],
NeSS-ST: Detecting Good and Stable Keypoints with a Neural Stability Score and the Shi-Tomasi detector,
ICCV23(9544-9554)
IEEE DOI Code:
WWW Link. 2401
BibRef

Santellani, E.[Emanuele], Sormann, C.[Christian], Rossi, M.[Mattia], Kuhn, A.[Andreas], Fraundorfer, F.[Friedrich],
S-TREK: Sequential Translation and Rotation Equivariant Keypoints for local feature extraction,
ICCV23(9694-9703)
IEEE DOI 2401
BibRef

Cao, C.J.[Chen-Jie], Fu, Y.W.[Yan-Wei],
Improving Transformer-based Image Matching by Cascaded Capturing Spatially Informative Keypoints,
ICCV23(12095-12105)
IEEE DOI 2401
BibRef

He, X.Z.[Xing-Zhe], Bharaj, G.[Gaurav], Ferman, D.[David], Rhodin, H.[Helge], Garrido, P.[Pablo],
Few-Shot Geometry-Aware Keypoint Localization,
CVPR23(21337-21348)
IEEE DOI 2309
BibRef

Yang, H.[Heng], Pavone, M.[Marco],
Object Pose Estimation with Statistical Guarantees: Conformal Keypoint Detection and Geometric Uncertainty Propagation,
CVPR23(8947-8958)
IEEE DOI 2309
BibRef

Potje, G.[Guilherme], Cadar, F.[Felipe], Araujo, A.[André], Martins, R.[Renato], Nascimento, E.R.[Erickson R.],
Enhancing Deformable Local Features by Jointly Learning to Detect and Describe Keypoints,
CVPR23(1306-1315)
IEEE DOI 2309
BibRef

Bai, Y.T.[Yu-Tong], Wang, A.[Angtian], Kortylewski, A.[Adam], Yuille, A.L.[Alan L.],
CoKe: Contrastive Learning for Robust Keypoint Detection,
WACV23(65-74)
IEEE DOI 2302
Training, Representation learning, Visualization, Technological innovation, Prototypes, Feature extraction, segmentation BibRef

Jin, D.[Dan], Xu, J.[Jian],
Integrated Deconvolution Keypoint Detector and Descriptor Network,
ICPR22(4885-4891)
IEEE DOI 2212
Training, Deconvolution, Neural networks, Lighting, Detectors, Task analysis BibRef

Qian, J.N.[Jia-Ning], Panagopoulos, A.[Anastasios], Jayaraman, D.[Dinesh],
Discovering Deformable Keypoint Pyramids,
ECCV22(XXVI:545-561).
Springer DOI 2211
BibRef

Fu, Y.J.[Yu-Jie], Rong, Z.[Zheng], Wu, Y.H.[Yi-Hong],
SRK-Net: Learning to Detect Repeatable Keypoints with Local Saliency Knowledge,
ICIP22(276-280)
IEEE DOI 2211
Training, Image edge detection, Detectors, Lead, Image Matching, Keypoint Detection, Local Saliency Knowledge BibRef

Sun, J.J.[Jennifer J.], Karashchuk, L.[Lili], Dravid, A.[Amil], Ryou, S.[Serim], Fereidooni, S.[Sonia], Tuthill, J.C.[John C.], Katsaggelos, A.[Aggelos], Brunton, B.W.[Bingni W.], Gkioxari, G.[Georgia], Kennedy, A.[Ann], Yue, Y.S.[Yi-Song], Perona, P.[Pietro],
BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos,
CVPR23(9001-9010)
IEEE DOI 2309
BibRef

Sun, J.J.[Jennifer J.], Ryou, S.[Serim], Goldshmid, R.H.[Roni H.], Weissbourd, B.[Brandon], Dabiri, J.O.[John O.], Anderson, D.J.[David J.], Kennedy, A.[Ann], Yue, Y.S.[Yi-Song], Perona, P.[Pietro],
Self-Supervised Keypoint Discovery in Behavioral Videos,
CVPR22(2161-2170)
IEEE DOI 2210
Training, Focusing, Manuals, Mice, Behavioral sciences, Spatiotemporal phenomena, Pattern recognition, Behavior analysis BibRef

Lee, J.[Jongmin], Kim, B.[Byungjin], Cho, M.[Minsu],
Self-Supervised Equivariant Learning for Oriented Keypoint Detection,
CVPR22(4837-4847)
IEEE DOI 2210
Training, Histograms, Image matching, Pose estimation, Self-supervised learning, Benchmark testing, Self- semi- meta- unsupervised learning BibRef

Yan, P.[Pei], Tan, Y.H.[Yi-Hua], Xiong, S.Z.[Sheng-Zhou], Tai, Y.[Yuan], Li, Y.S.[Yan-Sheng],
Learning Soft Estimator of Keypoint Scale and Orientation with Probabilistic Covariant Loss,
CVPR22(19384-19393)
IEEE DOI 2210
Point cloud compression, Image matching, Self-supervised learning, Probabilistic logic, Self- semi- meta- unsupervised learning BibRef

Lu, C.S.[Chang-Sheng], Koniusz, P.[Piotr],
Few-shot Keypoint Detection with Uncertainty Learning for Unseen Species,
CVPR22(19394-19404)
IEEE DOI 2210
Training, Location awareness, Representation learning, Visualization, Uncertainty, Statistical analysis, Visual reasoning BibRef

Ludwig, K.[Katja], Kienzle, D.[Daniel], Lienhart, R.[Rainer],
Recognition of Freely Selected Keypoints on Human Limbs,
CVSports22(3530-3538)
IEEE DOI 2210
Measurement, Image edge detection, Computational modeling, Biological system modeling, Pose estimation BibRef

Lu, D.C.[Dong-Chen], Li, D.M.[Dong-Mei], Li, Y.L.[Ya-Li], Wang, S.J.[Sheng-Jin],
OSKDet: Orientation-sensitive Keypoint Localization for Rotated Object Detection,
CVPR22(1172-1182)
IEEE DOI 2210
Location awareness, Heating systems, Uncertainty, Shape, Object detection, Detectors, Recognition: detection, Photogrammetry and remote sensing BibRef

You, Y.[Yang], Liu, W.H.[Wen-Hai], Ze, Y.J.[Yan-Jie], Li, Y.L.[Yong-Lu], Wang, W.M.[Wei-Ming], Lu, C.[Cewu],
UKPGAN: A General Self-Supervised Keypoint Detector,
CVPR22(17021-17030)
IEEE DOI 2210
Representation learning, Image analysis, Shape, Machine vision, Force, Estimation, Scene analysis and understanding, Self- semi- meta- Vision applications and systems BibRef

Zauss, D.[Duncan], Kreiss, S.[Sven], Alahi, A.[Alexandre],
Keypoint Communities,
ICCV21(11037-11046)
IEEE DOI 2203
Weight measurement, Training, Annotations, Pose estimation, Benchmark testing, Automobiles, Gestures and body pose, Vision for robotics and autonomous vehicles BibRef

Yang, S.[Sen], Quan, Z.B.[Zhi-Bin], Nie, M.[Mu], Yang, W.K.[Wan-Kou],
TransPose: Keypoint Localization via Transformer,
ICCV21(11782-11792)
IEEE DOI 2203
Location awareness, Heating systems, Training, Analytical models, Costs, Computational modeling, Pose estimation, Explainable AI BibRef

Lv, K.[Kai], Lu, Z.Q.[Zong-Qing], Liao, Q.M.[Qing-Min],
A Region-Based Descriptor Network for Uniformly Sampled Keypoints,
ICIP21(3278-3282)
IEEE DOI 2201
Training, Image processing, Cameras, Data mining, Task analysis, Keypoint extraction, feature descriptors, uniform sampling, deep learning BibRef

Shi, R.[Ruoxi], Xue, Z.R.[Zheng-Rong], You, Y.[Yang], Lu, C.[Cewu],
Skeleton Merger: an Unsupervised Aligned Keypoint Detector,
CVPR21(43-52)
IEEE DOI 2111
Charge coupled devices, Corporate acquisitions, Shape, Image edge detection, Refining, Detectors BibRef

Jiang, J.G.[Jun-Guang], Ji, Y.F.[Yi-Fei], Wang, X.[Ximei], Liu, Y.F.[Yu-Feng], Wang, J.M.[Jian-Min], Long, M.S.[Ming-Sheng],
Regressive Domain Adaptation for Unsupervised Keypoint Detection,
CVPR21(6776-6785)
IEEE DOI 2111
Training, Games, Superluminescent diodes, Minimization, Probability distribution, Generators BibRef

Chiberre, P.[Philippe], Perot, E.[Etienne], Sironi, A.[Amos], Lepetit, V.[Vincent],
Detecting Stable Keypoints from Events through Image Gradient Prediction,
EventVision21(1387-1394)
IEEE DOI 2109
E.g. Harris edges from event data itself. Image analysis, Detectors, Computer architecture, Streaming media, Cameras, Pattern recognition, Reliability BibRef

Yi-Ge, E.[Ellen], Fan, R.[Rui], Liu, Z.[Zechun], Shen, Z.Q.[Zhi-Qiang],
Conditional Link Prediction of Category-Implicit Keypoint Detection,
WACV21(3439-3448)
IEEE DOI 2106
Location awareness, Semantics, Estimation, Detectors, Benchmark testing, Feature extraction BibRef

Suwanwimolkul, S.[Suwichaya], Komorita, S.[Satoshi], Tasaka, K.[Kazuyuki],
Learning of low-level feature keypoints for accurate and robust detection,
WACV21(2261-2270)
IEEE DOI 2106
Measurement, Supervised learning, Detectors, Benchmark testing BibRef

Sidnev, A.[Alexey], Krasikova, E.[Ekaterina], Kazakov, M.[Maxim],
Efficient grouping for keypoint detection,
ICPR21(10712-10719)
IEEE DOI 2105
Training, Memory management, Pose estimation, Neural networks, Clothing, Pattern recognition, Acceleration BibRef

Vasconcelos, L.O.[Levi O.], Mancini, M.[Massimiliano], Boscaini, D.[Davide], Bulò, S.R.[Samuel Rota], Caputo, B.[Barbara], Ricci, E.[Elisa],
Shape Consistent 2D Keypoint Estimation under Domain Shift,
ICPR21(8037-8044)
IEEE DOI 2105
Training, Visualization, Shape, Semantics, Pose estimation, Deep architecture, Market research BibRef

Barroso-Laguna, A.[Axel], Verdie, Y.[Yannick], Busam, B.[Benjamin], Mikolajczyk, K.[Krystian],
HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning,
ACCV20(I:500-516).
Springer DOI 2103
BibRef

Tian, Y.[Yurun], Balntas, V.[Vassileios], Ng, T.[Tony], Barroso-Laguna, A.[Axel], Demiris, Y.[Yiannis], Mikolajczyk, K.[Krystian],
D2D: Keypoint Extraction with Describe to Detect Approach,
ACCV20(III:223-240).
Springer DOI 2103
BibRef

Jakab, T., Gupta, A., Bilen, H., Vedaldi, A.,
Self-Supervised Learning of Interpretable Keypoints From Unlabelled Videos,
CVPR20(8784-8794)
IEEE DOI 2008
Videos, Skeleton, Image reconstruction, Image recognition, Geometry, Decoding BibRef

Dong, Z., Li, G., Liao, Y., Wang, F., Ren, P., Qian, C.,
CentripetalNet: Pursuing High-Quality Keypoint Pairs for Object Detection,
CVPR20(10516-10525)
IEEE DOI 2008
Detectors, Feature extraction, Object detection, Training, Convolution, Heating systems BibRef

Zhang, Y.L.[Yi-Lun], Park, H.S.[Hyun Soo],
Multiview Supervision By Registration,
WACV20(409-417)
IEEE DOI 2006
Cameras, Detectors, Streaming media, Mice, Semisupervised learning, Geometry BibRef

Duan, K., Bai, S., Xie, L., Qi, H., Huang, Q., Tian, Q.,
CenterNet: Keypoint Triplets for Object Detection,
ICCV19(6568-6577)
IEEE DOI 2004
Code, Object Detection.
WWW Link. neural nets, object detection, MS-COCO dataset, representative one-stage keypoint-based detector, CenterNet, Task analysis BibRef

Yao, Y., Jafarian, Y., Park, H.S.,
MONET: Multiview Semi-Supervised Keypoint Detection via Epipolar Divergence,
ICCV19(753-762)
IEEE DOI 2004
computational complexity, image matching, image representation, learning (artificial intelligence), Image reconstruction BibRef

Pourian, N., Nestares, O.,
An End to End Framework to High Performance Geometry-Aware Multi-Scale Keypoint Detection and Matching in Fisheye Imag,
ICIP19(1302-1306)
IEEE DOI 1910
Keypoint Detection, Feature Matching, Fisheye, Epipolar Geometry, Spherical Projection BibRef

Faula, Y.[Yannick], Bres, S.[Stéphane], Eglin, V.[Véronique],
A Fast Local Analysis by Thresholding applied to image matching,
ICPR18(3055-3060)
IEEE DOI 1812
Detectors, Feature extraction, Image matching, Shape, Surface cracks, Image segmentation, Surface treatment BibRef

Georgakis, G., Karanam, S., Wu, Z., Ernst, J., Košecká, J.,
End-to-End Learning of Keypoint Detector and Descriptor for Pose Invariant 3D Matching,
CVPR18(1965-1973)
IEEE DOI 1812
Detectors, Task analysis, Proposals, Training, Feature extraction, Measurement BibRef

di Febbo, P., Dal Mutto, C., Tieu, K., Mattoccia, S.,
KCNN: Extremely-Efficient Hardware Keypoint Detection with a Compact Convolutional Neural Network,
ECVW18(795-7958)
IEEE DOI 1812
Detectors, Training, Computer architecture, Hardware, Field programmable gate arrays, Convolution, Complexity theory BibRef

Zhou, X.Y.[Xing-Yi], Karpur, A.[Arjun], Gan, C.[Chuang], Luo, L.J.[Lin-Jie], Huang, Q.X.[Qi-Xing],
Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency,
ECCV18(XII: 141-157).
Springer DOI 1810
BibRef

Zhou, X.Y.[Xing-Yi], Karpur, A.[Arjun], Luo, L.J.[Lin-Jie], Huang, Q.X.[Qi-Xing],
StarMap for Category-Agnostic Keypoint and Viewpoint Estimation,
ECCV18(I: 328-345).
Springer DOI 1810
BibRef

Huang, S., Gong, M., Tao, D.,
A Coarse-Fine Network for Keypoint Localization,
ICCV17(3047-3056)
IEEE DOI 1802
feature extraction, image matching, neural nets, object detection, pose estimation, 2016 COCO Keypoints Challenge dataset, CFN, CNNs, Proposals BibRef

Markuš, N.[Nenad], Pandžic, I.S.[Igor S.], Ahlberg, J.[Jörgen],
Learning local descriptors by optimizing the keypoint-correspondence criterion,
ICPR16(2380-2385)
IEEE DOI 1705
Computer architecture, Mathematical model, Neural networks, Standards, Training BibRef

Olson, C.F.[Clark F.], Hoover, S.A.[Sam A.], Soltman, J.L.[Jordan L.], Zhang, S.Q.[Si-Qi],
Complementary Keypoint Descriptors,
ISVC16(I: 341-352).
Springer DOI 1701
BibRef

Olson, C.F.[Clark F.], Zhang, S.Q.[Si-Qi],
Keypoint Recognition with Histograms of Normalized Colors,
CRV16(311-318)
IEEE DOI 1612
color; descriptor; keypoint; object recognition BibRef

St-Charles, P.L.[Pierre-Luc], Bilodeau, G.A.[Guillaume-Alexandre], Bergevin, R.[Robert],
Fast Image Gradients Using Binary Feature Convolutions,
Robust16(1074-1082)
IEEE DOI 1612
BibRef

Okutani, R., Sugimoto, K., Kamata, S.I.,
Efficient keypoint detection and description using filter kernel decomposition in scale space,
ICIP16(31-35)
IEEE DOI 1610
Computational complexity BibRef

Araujo, A., Lakshman, H., Angst, R., Girod, B.,
Modeling the impact of keypoint detection errors on local descriptor similarity,
ICIP16(305-309)
IEEE DOI 1610
Closed-form solutions BibRef

Yi, K.M.[Kwang Moo], Trulls, E.[Eduard], Lepetit, V.[Vincent], Fua, P.[Pascal],
LIFT: Learned Invariant Feature Transform,
ECCV16(VI: 467-483).
Springer DOI 1611
BibRef

Yi, K.M.[Kwang Moo], Verdie, Y.[Yannick], Fua, P.[Pascal], Lepetit, V.[Vincent],
Learning to Assign Orientations to Feature Points,
CVPR16(107-116)
IEEE DOI 1612
BibRef
Earlier: A2, A1, A3, A4:
TILDE: A Temporally Invariant Learned DEtector,
CVPR15(5279-5288)
IEEE DOI 1510
detect repeatable keypoints. BibRef

Danielsson, O.[Oscar],
Category-Sensitive Hashing and Bloom Filter Based Descriptors for Online Keypoint Recognition,
SCIA15(329-340).
Springer DOI 1506
BibRef

Gadelha, M.A.[Matheus A.], Carvalho, B.M.[Bruno M.],
DRINK: Discrete Robust Invariant Keypoints,
ICPR14(821-826)
IEEE DOI 1412
Brightness BibRef

Lee, S.[Suwon], Lee, S.W.[Sang-Wook], Chae, Y.N.[Yeong Nam], Yang, H.S.[Hyun S.],
Lightweight Random Ferns using binary representation,
ICPR12(1342-1345).
WWW Link. 1302
real-time keypoint recognition BibRef

Fragoso, V.[Victor], Turk, M.[Matthew], Hespanha, J.[Joao],
Locating binary features for keypoint recognition using noncooperative games,
ICIP12(2389-2392).
IEEE DOI 1302
BibRef

Martins, P.[Pedro], Carvalho, P.[Paulo], Gatta, C.[Carlo],
Stable Salient Shapes,
DICTA12(1-8).
IEEE DOI 1303
BibRef
And:
Context Aware Keypoint Extraction for Robust Image Representation,
BMVC12(100).
DOI Link 1301
BibRef

Alahi, A.[Alexandre], Ortiz, R.[Raphael], Vandergheynst, P.[Pierre],
FREAK: Fast Retina Keypoint,
CVPR12(510-517).
IEEE DOI 1208
vs. SIFT, SURF BibRef

Gauglitz, S.[Steffen], Turk, M.A.[Matthew A.], Höllerer, T.[Tobias],
Improving Keypoint Orientation Assignment,
BMVC11(xx-yy).
HTML Version. 1110
BibRef

Ventura, J.[Jonathan], Hollerer, T.[Tobias],
Fast and scalable keypoint recognition and image retrieval using binary codes,
WMVC11(697-702).
IEEE DOI 1101
BibRef

Rudinac, M.[Maja], Lenseigne, B.[Boris], Jonker, P.P.[Pieter P.],
Keypoint Extraction and Selection for Object Recognition,
MVA09(191-).
PDF File. 0905
BibRef

Marimon, D.[David], Bonnin, A.[Arturo], Adamek, T.[Tomasz], Gimeno, R.[Roger],
DARTs: Efficient scale-space extraction of DAISY keypoints,
CVPR10(2416-2423).
IEEE DOI 1006

See also Picking the best DAISY. BibRef

Jamshy, S.[Shahar], Krupka, E.[Eyal], Yeshurun, Y.[Yehezkel],
Reducing Keypoint Database Size,
CIAP09(113-122).
Springer DOI 0909
BibRef

Strecha, C.[Christoph], Lindner, A.[Albrecht], Ali, K.[Karim], Fua, P.[Pascal],
Training for Task Specific Keypoint Detection,
DAGM09(151-160).
Springer DOI 0909
Train interest point detector for only the task specific ones. BibRef

Herpers, R., Sommer, G., Michaelis, M., Witta, L.,
Context Based Detection of Keypoints and Features in Eye Regions,
ICPR96(II: 23-28).
IEEE DOI 9608
(GSF, D) BibRef

Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
HOG Analysis, Histogram of Oriented Gradient .


Last update:Mar 16, 2024 at 20:36:19