Nguyen, M.H.[Minh Hoai],
de la Torre, F.[Fernando],
Metric Learning for Image Alignment,
IJCV(88), No. 1, May 2010, pp. xx-yy.
Springer DOI
1003
BibRef
Earlier: A2, A1:
Parameterized Kernel Principal Component Analysis:
Theory and applications to supervised and unsupervised image alignment,
CVPR08(1-8).
IEEE DOI
0806
BibRef
And: A1, A2:
Learning image alignment without local minima for face detection and
tracking,
FG08(1-7).
IEEE DOI
0809
BibRef
Nguyen, M.H.[Minh Hoai],
de la Torre, F.[Fernando],
Local minima free Parameterized Appearance Models,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Zhang, F.H.[Fei-Hu],
Wah, B.W.[Benjamin W.],
Fundamental Principles on Learning New Features for Effective Dense
Matching,
IP(27), No. 2, February 2018, pp. 822-836.
IEEE DOI
1712
Benchmark testing, Colored noise, Feature extraction,
Image color analysis, Optical imaging, Radiometry, Time complexity,
stereo matching
BibRef
Chen, Y.[Yuan],
Jiang, J.[Jie],
A Two-Stage Deep Learning Registration Method for Remote Sensing
Images Based on Sub-Image Matching,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link
2109
BibRef
Fu, Y.J.[Yu-Jie],
Zhang, P.J.[Peng-Ju],
Liu, B.X.[Bing-Xi],
Rong, Z.[Zheng],
Wu, Y.H.[Yi-Hong],
Learning to Reduce Scale Differences for Large-Scale Invariant Image
Matching,
CirSysVideo(33), No. 3, March 2023, pp. 1335-1348.
IEEE DOI
2303
Feature extraction, Estimation, Detectors, Visualization,
Image matching, Convolutional neural networks, Task analysis,
covisibility-attention-reinforced matching module
BibRef
Li, Z.Z.[Zi-Zhuo],
Ma, Y.[Yong],
Mei, X.G.[Xiao-Guang],
Ma, J.Y.[Jia-Yi],
Two-view correspondence learning using graph neural network with
reciprocal neighbor attention,
PandRS(202), 2023, pp. 114-124.
Elsevier DOI
2308
WWW Link. Correspondence learning, Contextual information,
Reciprocal neighbor, Feature matching, Outlier rejection
BibRef
Fang, X.[Xiang],
Zhang, S.H.[Shi-Hua],
Zhang, H.[Hao],
Mei, X.G.[Xiao-Guang],
Zhou, H.[Huabing],
Ma, J.Y.[Jia-Yi],
Selecting and Pruning: A Differentiable Causal Sequentialized
State-Space Model for Two-View Correspondence Learning,
IP(35), 2026, pp. 816-829.
IEEE DOI Code:
WWW Link.
2602
Visualization, Matched filters, Information filters,
Feature extraction, Computational modeling, Complexity theory,
two-view geometry
BibRef
Li, X.H.[Xing-Hui],
Han, K.[Kai],
Li, S.[Shuda],
Prisacariu, V.[Victor],
DualRC: A Dual-Resolution Learning Framework With Neighbourhood
Consensus for Visual Correspondences,
PAMI(46), No. 1, January 2024, pp. 236-249.
IEEE DOI
2312
BibRef
Li, S.[Shuda],
Han, K.[Kai],
Costain, T.W.[Theo W.],
Howard-Jenkins, H.[Henry],
Prisacariu, V.[Victor],
Correspondence Networks With Adaptive Neighbourhood Consensus,
CVPR20(10193-10202)
IEEE DOI
2008
Feature extraction, Semantics, Correlation, Estimation,
Task analysis, Convolution, Robustness
BibRef
Shen, M.J.[Min-Jun],
Xiao, G.B.[Guo-Bao],
Yang, C.C.[Chang-Cai],
Guo, J.W.[Jun-Wen],
Zhu, L.[Lei],
CLG-Net: Rethinking Local and Global Perception in Lightweight
Two-View Correspondence Learning,
CirSysVideo(35), No. 1, January 2025, pp. 207-218.
IEEE DOI Code:
WWW Link.
2502
Transformers, Feature extraction, Convolution,
Learning systems, Deep learning, Accuracy,
lightweight transformer
BibRef
Ma, J.Y.[Jia-Yi],
Wang, Y.[Yang],
Fan, A.X.[Ao-Xiang],
Xiao, G.B.[Guo-Bao],
Chen, R.Q.[Ri-Qing],
Correspondence Attention Transformer:
A Context-Sensitive Network for Two-View Correspondence Learning,
MultMed(25), 2023, pp. 3509-3524.
IEEE DOI
2310
BibRef
Miao, X.Y.[Xiang-Yang],
Chen, S.X.[Shun-Xing],
Wang, S.P.[Shi-Ping],
Guo, J.W.[Jun-Wen],
Wu, F.Y.[Feng-Ying],
Xiao, G.B.[Guo-Bao],
Li, Z.J.[Zong-Juan],
PTCNet: Pure transformer network for two-view correspondence pruning,
PR(179), 2026, pp. 113564.
Elsevier DOI Code:
WWW Link.
2606
Feature matching, Correspondence pruning, Outlier rejection, Transformer
BibRef
Yang, C.C.[Chang-Cai],
Li, X.J.[Xiao-Jie],
Ma, J.Y.[Jia-Yi],
Zhuang, F.Y.[Feng-Yuan],
Wei, L.F.[Li-Fang],
Chen, R.Q.[Ri-Qing],
Chen, G.D.[Guo-Dong],
CGR-Net: Consistency Guided ResFormer for Two-View Correspondence
Learning,
CirSysVideo(34), No. 12, December 2024, pp. 12450-12465.
IEEE DOI Code:
WWW Link.
2501
Task analysis, Feature extraction, Forestry, Accuracy,
Smoothing methods, Pipelines, Convolutional neural networks,
graph convolutional neural network
BibRef
Shi, Z.W.[Zi-Wei],
Miao, X.Y.[Xiang-Yang],
Xiao, G.B.[Guo-Bao],
Du, S.L.[Song-Lin],
Wang, Z.[Zheng],
Shen, H.T.[Heng Tao],
Topology Learning for Two-View Correspondence Filtering,
MultMed(27), 2025, pp. 7533-7545.
IEEE DOI
2510
Topology, Network topology, Filtering, Transformers, Feature extraction,
Data mining, Reliability, Attention mechanisms, transformer
BibRef
Liu, X.[Xin],
Xiao, G.B.[Guo-Bao],
Chen, R.Q.[Ri-Qing],
Ma, J.Y.[Jia-Yi],
PGFNet: Preference-Guided Filtering Network for Two-View
Correspondence Learning,
IP(32), 2023, pp. 1367-1378.
IEEE DOI
2303
Reliability, Task analysis, Iterative methods, Feature extraction,
Cameras, Filtering, Computer network reliability,
camera pose estimation
BibRef
Liao, T.F.[Tang-Fei],
Zhang, X.Q.[Xiao-Qin],
Xu, Y.W.[Yue-Wang],
Shi, Z.W.[Zi-Wei],
Xiao, G.B.[Guo-Bao],
SGA-Net: A Sparse Graph Attention Network for Two-View Correspondence
Learning,
CirSysVideo(33), No. 12, December 2023, pp. 7578-7590.
IEEE DOI
2312
BibRef
Lin, S.Y.[Shu-Yuan],
Guo, Y.[Yu],
Chen, X.[Xiao],
Liang, Y.J.[Yan-Jie],
Xiao, G.B.[Guo-Bao],
Huang, F.[Feiran],
LLHA-Net: A hierarchical attention network for two-view
correspondence learning,
PR(173), 2026, pp. 112896.
Elsevier DOI Code:
WWW Link.
2601
Correspondence learning, Feature matching, Outlier removal,
Camera pose estimation, Hierarchical attention
BibRef
Yang, M.[Meng],
Chen, J.[Jun],
Tian, X.[Xin],
Wei, L.S.[Long-Sheng],
Ma, J.Y.[Jia-Yi],
VRTNet: Vector Rectifier Transformer for Two-View Correspondence
Learning,
MultMed(27), 2025, pp. 515-530.
IEEE DOI
2502
Vectors, Transformers, Rectifiers, Decoding, Feature extraction,
Convolution, Data mining, Transforms, Image registration,
context and channel information
BibRef
Xiao, G.B.[Guo-Bao],
Liu, X.[Xin],
Zhong, Z.[Zhen],
Zhang, X.Q.[Xiao-Qin],
Ma, J.Y.[Jia-Yi],
Ling, H.B.[Hai-Bin],
T-Net++: Effective Permutation-Equivariance Network for Two-View
Correspondence Pruning,
PAMI(46), No. 12, December 2024, pp. 10629-10644.
IEEE DOI
2411
Feature extraction, Task analysis, Accuracy, Learning systems,
Iterative methods, Benchmark testing, Uncertainty,
permutation-equivariance
BibRef
Zhong, Z.[Zhen],
Xiao, G.B.[Guo-Bao],
Zheng, L.X.[Lin-Xin],
Lu, Y.[Yan],
Ma, J.Y.[Jia-Yi],
T-Net: Effective Permutation-Equivariant Network for Two-View
Correspondence Learning,
ICCV21(1930-1939)
IEEE DOI
2203
Geometry, Codes, Pose estimation, Cameras,
Task analysis, Computational photography,
Gestures and body pose
BibRef
Zhang, S.H.[Shi-Hua],
Ma, J.Y.[Jia-Yi],
ConvMatch: Rethinking Network Design for Two-View Correspondence
Learning,
PAMI(46), No. 5, May 2024, pp. 2920-2935.
IEEE DOI
2404
Convolutional neural networks, Feature extraction, Geometry,
Visualization, Location awareness, Pipelines, Convolution,
two-view geometry
BibRef
Sippel, F.[Frank],
Seiler, J.[Jürgen],
Kaup, A.[André],
Multispectral Snapshot Image Registration Using Learned Cross
Spectral Disparity Estimation and a Deep Guided Occlusion
Reconstruction Network,
IP(34), 2025, pp. 2338-2350.
IEEE DOI Code:
WWW Link.
2505
Cameras, Image registration, Image reconstruction, Arrays, Estimation,
Calibration, Pipelines, Videos, Costs, Neural networks, image registration
BibRef
Chen, K.[Ke],
Han, H.[Huan],
Wei, J.P.[Jun-Ping],
Zhang, Y.M.[Yi-Min],
A Novel Few-Shot Learning Framework for Supervised Diffeomorphic
Image Registration Network,
MedImg(44), No. 12, December 2025, pp. 4903-4917.
IEEE DOI Code:
WWW Link.
2512
Image registration, Training, Few shot learning, Deformation,
Numerical models, Biomedical imaging, Real-time systems, few-shot learning
BibRef
Zhou, Y.[Yu],
Liu, J.B.[Jian-Bin],
Zheng, H.[Huaibin],
Chen, H.[Hui],
He, Y.C.[Yu-Chen],
Li, F.[Fuli],
Xu, Z.[Zhuo],
Bridging optics and machine learning: revisiting correspondence
imaging via linear classification,
JOSA-A(43), No. 3, March 2026, pp. 535-544.
DOI Link
2603
Computational imaging, Ghost imaging, Imaging systems,
Machine learning, Neural networks, Optical computing
BibRef
Guo, S.X.[Shao-Xiang],
Risbridger, D.[Donald],
Robb, D.A.[David A.],
Kong, X.[Xianwen],
Esser, M.J.D.[M. J. Daniel],
Chantler, M.J.[Michael J.],
Carter, R.M.[Richard M.],
Erden, M.S.[Mustafa Suphi],
A two-stage learning framework with a beam image dataset for
automatic laser resonator alignment,
PR(176), 2026, pp. 113145.
Elsevier DOI
2603
Pattern recognition, Beam image dataset, Optical alignment,
Pairwise image regression, Convolutional neural network, Transformer
BibRef
Sousa, J.[João],
Darabi, R.[Roya],
Sousa, A.[Armando],
Brueckner, F.[Frank],
Reis, L.P.[Luís Paulo],
Reis, A.[Ana],
JEMA: Joint Embedding of Multimodal and multi-view Alignment in
human-centric embedding space for manufacturing,
CVIU(268), 2026, pp. 104771.
Elsevier DOI
2605
Artificial intelligence, Transference,
Embedding representation, Contrastive learning, Additive manufacturing
BibRef
Shi, L.[Lin],
Wang, R.[Renzhen],
Zhu, X.F.[Xiao-Feng],
An, C.[Cong],
Zhao, K.[Kai],
Shu, J.[Jun],
Yang, D.F.[Dong-Fang],
Meng, D.Y.[De-Yu],
Bi-Level Meta-Learning for Reliable Remote Sensing Image Registration,
RS(18), No. 12, 2026, pp. 2007.
DOI Link
2606
BibRef
El Banani, M.[Mohamed],
Rocco, I.[Ignacio],
Novotny, D.[David],
Vedaldi, A.[Andrea],
Neverova, N.[Natalia],
Johnson, J.[Justin],
Graham, B.[Ben],
Self-supervised Correspondence Estimation via Multiview Registration,
WACV23(1216-1225)
IEEE DOI
2302
Visualization, Pipelines, Video sequences, Estimation, Training data,
Algorithms: 3D computer vision, Machine learning architectures
BibRef
Han, K.[Kun],
Sun, S.L.[Shan-Lin],
Yan, X.Y.[Xiang-Yi],
You, C.Y.[Chen-Yu],
Tang, H.[Hao],
Naushad, J.[Junayed],
Ma, H.Y.[Hao-Yu],
Kong, D.Y.[De-Ying],
Xie, X.H.[Xiao-Hui],
Diffeomorphic Image Registration with Neural Velocity Field,
WACV23(1869-1879)
IEEE DOI
2302
Deformable models, Learning systems, Deep learning,
Image registration, Neural networks, Brain modeling,
visual reasoning
BibRef
Pal, S.[Soumyadeep],
Tennant, M.[Matthew],
Ray, N.[Nilanjan],
Towards Positive Jacobian: Learn to Postprocess for Diffeomorphic
Image Registration with Matrix Exponential,
ICPR22(3391-3398)
IEEE DOI
2212
Jacobian matrices, Deep learning, Image registration,
Poisson equations, Pipelines
BibRef
Mao, R.[Runyu],
Bai, C.[Chen],
An, Y.[Yatong],
Zhu, F.Q.[Feng-Qing],
Lu, C.[Cheng],
3DG-STFM: 3D Geometric Guided Student-Teacher Feature Matching,
ECCV22(XXVIII:125-142).
Springer DOI
2211
WWW Link.
BibRef
Peebles, W.[William],
Zhu, J.Y.[Jun-Yan],
Zhang, R.[Richard],
Torralba, A.[Antonio],
Efros, A.A.[Alexei A.],
Shechtman, E.[Eli],
GAN-Supervised Dense Visual Alignment,
CVPR22(13460-13471)
IEEE DOI
2210
Training, Visualization, Training data, Transformers, Data models, Vision + graphics
BibRef
Mok, T.C.W.[Tony C. W.],
Chung, A.C.S.[Albert C. S.],
Affine Medical Image Registration with Coarse-to-Fine Vision
Transformer,
CVPR22(20803-20812)
IEEE DOI
2210
Training, Learning systems, Convolutional codes,
Image registration, Runtime, Transformers, Medical,
biological and cell microscopy
BibRef
Zeng, X.R.[Xiang-Rui],
Howe, G.[Gregory],
Xu, M.[Min],
End-to-end robust joint unsupervised image alignment and clustering,
ICCV21(3834-3846)
IEEE DOI
2203
Training, Systematics, Computational modeling, Semantics,
Benchmark testing, Medical, biological, and cell microscopy,
Transfer/Low-shot/Semi/Unsupervised Learning
BibRef
Heinrich, K.,
Mehltretter, M.,
Learning Multi-modal Features for Dense Matching-based Confidence
Estimation,
ISPRS21(B2-2021: 91-99).
DOI Link
2201
BibRef
Krishna, O.[Onkar],
Irie, G.[Go],
Wu, X.M.[Xiao-Meng],
Kimura, A.[Akisato],
Kashino, K.[Kunio],
Deep Reinforcement Image Matching with Self-Termination,
ICIP21(1254-1258)
IEEE DOI
2201
Recurrent neural networks, Image matching, Image processing,
Reinforcement learning, History, deep reinforcement learning,
self-termination
BibRef
Tang, J.P.[Jia-Peng],
Xu, D.[Dan],
Jia, K.[Kui],
Zhang, L.[Lei],
Learning Parallel Dense Correspondence from Spatio-Temporal
Descriptors for Efficient and Robust 4D Reconstruction,
CVPR21(6018-6027)
IEEE DOI
2111
Geometry, Surface reconstruction,
Shape, Computational modeling, Pipelines
BibRef
Al Safadi, E.[Ebrahim],
Song, X.[Xubo],
Learning-based Image Registration with Meta-Regularization,
CVPR21(10923-10932)
IEEE DOI
2111
Optical filters, Deformable models, Training, Image registration,
Filtering theory, Registers
BibRef
Jiang, S.Y.[Shi-Yan],
Wang, C.[Ci],
Huang, C.[Chang],
Image Registration Improved by Generative Adversarial Networks,
MMMod21(II:26-35).
Springer DOI
2106
BibRef
Darmon, F.,
Aubry, M.,
Monasse, P.[Pascal],
Learning to Guide Local Feature Matches,
3DV20(1127-1136)
IEEE DOI
2102
Geometry, Correlation, Feature extraction,
Training, Image matching, Detectors, 3D reconstruction
BibRef
Yu, H.H.,
Liu, J.,
Sun, H.,
Wang, Z.,
Zhang, H.,
GetNet: Get Target Area for Image Pairing,
IVCNZ19(1-6)
IEEE DOI
2004
evolutionary computation,
learning (artificial intelligence), neural nets, image matching.
BibRef
Jiang, W.[Wei],
Trulls, E.[Eduard],
Hosang, J.[Jan],
Tagliasacchi, A.[Andrea],
Yi, K.M.[Kwang Moo],
COTR: Correspondence Transformer for Matching Across Images,
ICCV21(6187-6197)
IEEE DOI
2203
Deep learning, Codes, Pipelines, Neural networks, Transformers,
Reproducibility of results, Stereo,
Low-level and physics-based vision
BibRef
Niethammer, M.[Marc],
Kwitt, R.[Roland],
Vialard, F.X.[Francois-Xavier],
Metric Learning for Image Registration,
CVPR19(8455-8464).
IEEE DOI
2002
BibRef
Quan, D.[Dou],
Fang, S.[Shuai],
Liang, X.F.[Xue-Feng],
Wang, S.[Shuang],
Jiao, L.C.[Li-Cheng],
Cross-Spectral Image Patch Matching by Learning Features of the
Spatially Connected Patches in a Shared Space,
ACCV18(II:115-130).
Springer DOI
1906
BibRef
Dong, J.,
Boots, B.,
Dellaert, F.,
Chandra, R.,
Sinha, S.,
Learning to Align Images Using Weak Geometric Supervision,
3DV18(700-709)
IEEE DOI
1812
convolution, feature extraction, feedforward neural nets,
image matching, learning (artificial intelligence),
weakly-supervised learning
BibRef
Yang, D.[Di],
Li, H.D.[Hong-Dong],
Learning varying dimension radial basis functions for deformable image
alignment,
NORDIA09(344-351).
IEEE DOI
0910
BibRef
El-Baz, A.S.[Ayman S.],
Gimel'farb, G.L.[Georgy L.],
Global image registration based on learning the prior appearance model,
CVPR08(1-7).
IEEE DOI
0806
BibRef
El-Baz, A.S.[Ayman S.],
Farag, A.A.[Aly A.],
Gimel'farb, G.L.[Georgy L.],
Abdel-Hakim, A.E.[Alaa E.],
Image Alignment Using Learning Prior Appearance Model,
ICIP06(341-344).
IEEE DOI
0610
BibRef
Earlier:
Robust Image Registration Based on Markov-Gibbs Appearance Model,
ICPR06(II: 1204-1207).
IEEE DOI
0609
BibRef
El-Baz, A.S.[Ayman S.],
Farag, A.A.[Aly A.],
Gimel'farb, G.L.[Georgy L.],
Experiments on Robust Image Registration Using a Markov-Gibbs
Appearance Model,
SSPR06(65-73).
Springer DOI
0608
BibRef
Ham, J.[Jihun],
Ahn, I.[Ikkjin],
Lee, D.[Daniel],
Learning a manifold-constrained map between image sets:
Applications to matching and pose estimation,
CVPR06(I: 817-824).
IEEE DOI
0606
Model based matching.
BibRef
Chen, B.[Bo],
Chin, T.J.[Tat-Jun],
Klimavicius, M.[Marius],
Occlusion-Robust Object Pose Estimation with Holistic Representation,
WACV22(2223-2233)
IEEE DOI
2202
Representation learning, Measurement, Technological innovation,
Codes, Computational modeling, Pose estimation,
Deep Learning object pose estimation
BibRef
Chapter on Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces continues in
Image Registration -- The Match Technique, Match Measures, Cost Function .