Equinox: Human Identification at a Distance,
HID. 2006.
IR images available.
Face Recognition.
HTML Version.
Dataset, Faces.
See also Equinox Corporation.
Medioni, G.,
Choi, J.M.[Jong-Moo],
Kuo, C.H.[Cheng-Hao],
Fidaleo, D.,
Identifying Noncooperative Subjects at a Distance Using Face Images and
Inferred Three-Dimensional Face Models,
SMC-A(39), No. 1, January 2009, pp. 12-24.
IEEE DOI
0901
Recongition at a distance.
BibRef
Medioni, G.,
Choi, J.M.[Jong-Moo],
Kuo, C.H.[Cheng-Hao],
Choudhury, A.,
Zhang, L.[Li],
Fidaleo, D.,
Non-Cooperative Persons Identification at a Distance with 3D Face
Modeling,
BTAS07(1-6).
IEEE DOI
0709
BibRef
Bhanu, B.[Bir],
Han, J.[Ju],
Human Recognition at a Distance in Video,
Springer2010, ISBN: 978-0-85729-123-3
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Chen, X.J.[Xiao-Jing],
An, L.[Le],
Bhanu, B.[Bir],
Improving large-scale face image retrieval using multi-level features,
ICIP13(4367-4371)
IEEE DOI
1402
Face retrieval; large-scale; multi-level features
BibRef
An, L.[Le],
Bhanu, B.[Bir],
Yang, S.F.[Song-Fan],
Boosting Face Recognition in Real-World Surveillance Videos,
AVSS12(270-275).
IEEE DOI
1211
BibRef
Ren, C.X.,
Dai, D.Q.,
Yan, H.,
Coupled Kernel Embedding for Low-Resolution Face Image Recognition,
IP(21), No. 8, August 2012, pp. 3770-3783.
IEEE DOI
1208
BibRef
Ren, C.X.[Chuan-Xian],
Dai, D.Q.[Dao-Qing],
Li, X.X.[Xiao-Xin],
Lai, Z.R.[Zhao-Rong],
Band-Reweighed Gabor Kernel Embedding for Face Image Representation
and Recognition,
IP(23), No. 2, February 2014, pp. 725-740.
IEEE DOI
1402
Gabor filters
BibRef
Ren, C.X.[Chuan-Xian],
Lei, Z.,
Dai, D.Q.[Dao-Qing],
Li, S.Z.,
Enhanced Local Gradient Order Features and Discriminant Analysis for
Face Recognition,
Cyber(46), No. 11, November 2016, pp. 2656-2669.
IEEE DOI
1609
face recognition
BibRef
Lai, Z.R.[Zhao-Rong],
Dai, D.Q.[Dao-Qing],
Ren, C.X.[Chuan-Xian],
Huang, K.K.[Ke-Kun],
Discriminative and Compact Coding for Robust Face Recognition,
Cyber(45), No. 9, September 2015, pp. 1900-1912.
IEEE DOI
1509
face recognition
BibRef
Lai, Z.R.[Zhao-Rong],
Dai, D.Q.[Dao-Qing],
Ren, C.X.[Chuan-Xian],
Huang, K.K.[Ke-Kun],
Multiscale Logarithm Difference Edgemaps for Face Recognition Against
Varying Lighting Conditions,
IP(24), No. 6, June 2015, pp. 1735-1747.
IEEE DOI
1504
Face recognition
BibRef
Ren, C.X.[Chuan-Xian],
Dai, D.Q.[Dao-Qing],
Huang, K.K.[Ke-Kun],
Lai, Z.R.[Zhao-Rong],
Transfer Learning of Structured Representation for Face Recognition,
IP(23), No. 12, December 2014, pp. 5440-5454.
IEEE DOI
1412
face recognition
BibRef
Lai, Z.R.[Zhao-Rong],
Dai, D.Q.[Dao-Qing],
Ren, C.X.[Chuan-Xian],
Huang, K.,
Multilayer Surface Albedo for Face Recognition With Reference Images
in Bad Lighting Conditions,
IP(23), No. 11, November 2014, pp. 4709-4723.
IEEE DOI
1410
Discrete cosine transforms
BibRef
Biswas, S.[Soma],
Bowyer, K.W.[Kevin W.],
Flynn, P.J.[Patrick J.],
Multidimensional Scaling for Matching Low-Resolution Face Images,
PAMI(34), No. 10, October 2012, pp. 2019-2030.
IEEE DOI
1208
Embed the low-res test image and the high-res database image
in a common space such that the distance between them
in the transformed space approximates the distance
if both were high res.
BibRef
Chellappa, R.[Rama],
Ni, J.[Jie],
Patel, V.M.[Vishal M.],
Remote identification of faces: Problems, prospects, and progress,
PRL(33), No. 14, 15 October 2012, pp. 1849-1859.
Elsevier DOI
1209
Remote face recognition; Re-identification; Illumination; Blur;
Low-resolution; Pose variation
BibRef
Vageeswaran, P.,
Mitra, K.,
Chellappa, R.,
Blur and Illumination Robust Face Recognition via Set-Theoretic
Characterization,
IP(22), No. 4, April 2013, pp. 1362-1372.
IEEE DOI
1303
BibRef
Kan, M.,
Xu, D.[Dong],
Shan, S.G.[Shi-Guang],
Li, W.[Wen],
Chen, X.L.[Xi-Lin],
Learning Prototype Hyperplanes for Face Verification in the Wild,
IP(22), No. 8, 2013, pp. 3310-3316.
IEEE DOI
1307
Face verification in the wild; mid-level feature representation;
prototype hyperplane learning
BibRef
Kan, M.[Meina],
Xu, D.[Dong],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Semisupervised Hashing via Kernel Hyperplane Learning for Scalable
Image Search,
CirSysVideo(24), No. 4, April 2014, pp. 704-713.
IEEE DOI
1405
content-based retrieval
BibRef
Li, Y.[Yan],
Wang, R.P.[Rui-Ping],
Cui, Z.[Zhen],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Spatial Pyramid Covariance-Based Compact Video Code for Robust Face
Retrieval in TV-Series,
IP(25), No. 12, December 2016, pp. 5905-5919.
IEEE DOI
1612
BibRef
Earlier: A1, A2, A4, A5, Only:
Hierarchical hybrid statistic based video binary code and its
application to face retrieval in TV-series,
FG15(1-8)
IEEE DOI
1508
computational complexity
BibRef
Liu, H.M.[Hao-Miao],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Deep Supervised Hashing for Fast Image Retrieval,
IJCV(127), No. 9, September 2019, pp. 1217-1234.
Springer DOI
1908
BibRef
Earlier:
CVPR16(2064-2072)
IEEE DOI
1612
BibRef
Li, Y.[Yan],
Wang, R.P.[Rui-Ping],
Liu, H.M.[Hao-Miao],
Jiang, H.J.[Hua-Jie],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Two Birds, One Stone: Jointly Learning Binary Code for Large-Scale
Face Image Retrieval and Attributes Prediction,
ICCV15(3819-3827)
IEEE DOI
1602
Large-scale face image retrieval. Given and example, find others.
Binary codes; Birds; Face; Image retrieval; Semantics; Visualization
See also Learning Multifunctional Binary Codes for Both Category and Attribute Oriented Retrieval Tasks.
BibRef
Cui, Z.[Zhen],
Li, W.[Wen],
Xu, D.[Dong],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Fusing Robust Face Region Descriptors via Multiple Metric Learning
for Face Recognition in the Wild,
CVPR13(3554-3561)
IEEE DOI
1309
BibRef
Wang, Z.F.[Zhi-Fei],
Miao, Z.J.[Zhen-Jiang],
Wu, Q.M.J.[Q. M. Jonathan],
Wan, Y.L.[Yan-Li],
Tang, Z.[Zhen],
Low-resolution face recognition: a review,
VC(30), No. 4, April 2014, pp. 359-386.
WWW Link.
1404
Survey, Face Recognition.
BibRef
Kang, D.[Dongoh],
Han, H.[Hu],
Jain, A.K.[Anil K.],
Lee, S.W.[Seong-Whan],
Nighttime face recognition at large standoff:
Cross-distance and cross-spectral matching,
PR(47), No. 12, 2014, pp. 3750-3766.
Elsevier DOI
1410
Nighttime face recognition
BibRef
Maeng, H.J.[Hyun-Ju],
Liao, S.C.[Sheng-Cai],
Kang, D.[Dongoh],
Lee, S.W.[Seong-Whan],
Jain, A.K.[Anil K.],
Nighttime Face Recognition at Long Distance:
Cross-Distance and Cross-Spectral Matching,
ACCV12(II:708-721).
Springer DOI
1304
BibRef
Shi, J.G.[Jin-Gang],
Qi, C.[Chun],
From Local Geometry to Global Structure:
Learning Latent Subspace for Low-resolution Face Image Recognition,
SPLetters(22), No. 5, May 2015, pp. 554-558.
IEEE DOI
1411
BibRef
Earlier:
Face hallucination based on PCA dictionary pairs,
ICIP13(933-937)
IEEE DOI
1402
Dictionaries
Face
BibRef
Liu, L.[Luoqi],
Zhang, L.[Li],
Liu, H.R.[Hai-Rong],
Yan, S.C.[Shui-Cheng],
Toward Large-Population Face Identification in Unconstrained Videos,
CirSysVideo(24), No. 11, November 2014, pp. 1874-1884.
IEEE DOI
1411
face recognition
BibRef
Rim, D.[David],
Hasan, M.K.[Md Kamrul],
Puech, F.[Fannie],
Pal, C.J.[Christopher J.],
Learning from weakly labeled faces and video in the wild,
PR(48), No. 3, 2015, pp. 759-771.
Elsevier DOI
1412
Semi-supervised learning
BibRef
Ding, C.,
Xu, C.,
Tao, D.,
Multi-Task Pose-Invariant Face Recognition,
IP(24), No. 3, March 2015, pp. 980-993.
IEEE DOI
1502
Dictionaries
BibRef
Ding, C.,
Tao, D.,
Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based
Face Recognition,
PAMI(40), No. 4, April 2018, pp. 1002-1014.
IEEE DOI
1804
face recognition, feature extraction, image representation,
learning (artificial intelligence), neural nets,
video surveillance
BibRef
Ding, C.,
Tao, D.,
Robust Face Recognition via Multimodal Deep Face Representation,
MultMed(17), No. 11, November 2015, pp. 2049-2058.
IEEE DOI
1511
Databases
BibRef
Ding, C.X.[Chang-Xing],
Choi, J.H.[Jong-Hyun],
Tao, D.C.[Da-Cheng],
Davis, L.S.[Larry S.],
Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face
Recognition,
PAMI(38), No. 3, March 2016, pp. 518-531.
IEEE DOI
1602
Face. Unconstrained, illumination, pose, expression.
MDML-DCP. First derivative of Gaussian.
BibRef
Ding, C.X.[Chang-Xing],
Tao, D.C.[Da-Cheng],
Pose-invariant face recognition with homography-based normalization,
PR(66), No. 1, 2017, pp. 144-152.
Elsevier DOI
1704
Pose-invariant face recognition
BibRef
Huang, Z.W.[Zhi-Wu],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Face recognition on large-scale video in the wild with hybrid
Euclidean-and-Riemannian metric learning,
PR(48), No. 10, 2015, pp. 3113-3124.
Elsevier DOI
1507
BibRef
And:
Projection Metric Learning on Grassmann Manifold with Application to
Video based Face Recognition,
CVPR15(140-149)
IEEE DOI
1510
BibRef
Earlier:
Hybrid Euclidean-and-Riemannian Metric Learning for Image Set
Classification,
ACCV14(III: 562-577).
Springer DOI
1504
BibRef
And:
Learning Euclidean-to-Riemannian Metric for Point-to-Set
Classification,
CVPR14(1677-1684)
IEEE DOI
1409
Face recognition.
Euclidean-to-Riemannian metric learning; point-to-set classification
Single point matched to sets of correlated points.
BibRef
Huang, Z.W.[Zhi-Wu],
Wang, R.P.[Rui-Ping],
Shan, S.G.[Shi-Guang],
Van Gool, L.J.[Luc J.],
Chen, X.L.[Xi-Lin],
Cross Euclidean-to-Riemannian Metric Learning with Application to
Face Recognition from Video,
PAMI(40), No. 12, December 2018, pp. 2827-2840.
IEEE DOI
1811
Manifolds, Extraterrestrial measurements, Face recognition,
Learning systems, Riemannian manifold,
cross Euclidean-to-Riemannian metric learning
BibRef
Al-Maadeed, S.[Somaya],
Bourif, M.[Mehdi],
Bouridane, A.[Ahmed],
Jiang, R.[Richard],
Low-quality facial biometric verification via dictionary-based random
pooling,
PR(52), No. 1, 2016, pp. 238-248.
Elsevier DOI
1601
Facial biometrics
BibRef
Sagonas, C.[Christos],
Antonakos, E.[Epameinondas],
Tzimiropoulos, G.[Georgios],
Zafeiriou, S.P.[Stefanos P.],
Pantic, M.[Maja],
300 Faces In-The-Wild Challenge: database and results,
IVC(47), No. 1, 2016, pp. 3-18.
Elsevier DOI
1605
BibRef
Earlier: A1, A3, A4, A5, Only:
300 Faces in-the-Wild Challenge:
The First Facial Landmark Localization Challenge,
FaceWild13(397-403)
IEEE DOI
1403
Facial landmark localization.
BibRef
Tzimiropoulos, G.[Georgios],
Pantic, M.[Maja],
Optimization Problems for Fast AAM Fitting in-the-Wild,
ICCV13(593-600)
IEEE DOI
1403
AAMs; Active Appearance Models; Face alignment; In-the-wild
BibRef
Zafeiriou, S.P.[Stefanos P.],
Tzimiropoulos, G.[Georgios],
Pantic, M.[Maja],
300 W: Special issue on facial landmark localisation 'in-the-wild',
IVC(47), No. 1, 2016, pp. 1-2.
Elsevier DOI
1605
BibRef
Lin, Y.M.[Yi-Ming],
Shen, J.[Jie],
Wang, Y.J.[Yu-Jiang],
Pantic, M.[Maja],
RoI Tanh-polar transformer network for face parsing in the wild,
IVC(112), 2021, pp. 104190.
Elsevier DOI
2107
Face parsing, In-the-wild dataset, Head pose augmentation,
Tanh-polar representation
BibRef
Arashloo, S.R.[S. Rahimzadeh],
A comparison of deep multilayer networks and Markov random field
matching models for face recognition in the wild,
IET-CV(10), No. 6, 2016, pp. 466-474.
DOI Link
1609
Markov processes
BibRef
López, M.B.[Miguel Bordallo],
Boutellaa, E.[Elhocine],
Hadid, A.[Abdenour],
López, M.B.,
Boutellaa, E.,
Hadid, A.,
Comments on the 'Kinship Face in the Wild' Data Sets,
PAMI(38), No. 11, November 2016, pp. 2342-2344.
IEEE DOI
1610
Reccomends not using the existing data set due to issues in how it was
created. I.e. simple features relate to imaging methods can perform better
than real algorithms.
BibRef
Proença, H.[Hugo],
Neves, J.C.[João C.],
Barra, S.[Silvio],
Marques, T.,
Moreno, J.C.,
Joint Head Pose/Soft Label Estimation for Human Recognition
In-The-Wild,
PAMI(38), No. 12, December 2016, pp. 2444-2456.
IEEE DOI
1609
Biometrics (access control)
BibRef
Huang, C.T.[Chun-Ting],
Wang, Z.N.[Zheng-Ning],
Kuo, C.C.J.[C.C. Jay],
Visible-light and near-infrared face recognition at a distance,
JVCIR(41), No. 1, 2016, pp. 140-153.
Elsevier DOI
1612
BibRef
Earlier:
TAEF: A cross-distance/environment face recognition method,
Biometrics15(1-8)
IEEE DOI
1510
Face recognition.
Active appearance model
BibRef
Huber, P.,
Kopp, P.,
Christmas, W.,
Rätsch, M.,
Kittler, J.V.,
Real-Time 3D Face Fitting and Texture Fusion on In-the-Wild Videos,
SPLetters(24), No. 4, April 2017, pp. 437-441.
IEEE DOI
1704
face recognition
BibRef
Chen, J.[Jie],
Patel, V.M.[Vishal M.],
Liu, L.[Li],
Kellokumpu, V.[Vili],
Zhao, G.Y.[Guo-Ying],
Pietikäinen, M.[Matti],
Chellappa, R.[Rama],
Robust local features for remote face recognition,
IVC(64), No. 1, 2017, pp. 34-46.
Elsevier DOI
1708
Robust, local, feature
BibRef
Deng, W.,
Chen, B.,
Fang, Y.,
Hu, J.,
Deep Correlation Feature Learning for Face Verification in the Wild,
SPLetters(24), No. 12, December 2017, pp. 1877-1881.
IEEE DOI
1712
backpropagation, correlation methods, face recognition,
feedforward neural nets, vectors, 64-layer ResNet, CNN, DCFL network,
softmax
BibRef
Kumar, V.[Vijay],
Namboodiri, A.M.[Anoop M.],
Jawahar, C.V.,
Semi-supervised annotation of faces in image collection,
SIViP(12), No. 1, January 2018, pp. 141-149.
WWW Link.
1801
BibRef
Earlier:
Visual Phrases for Exemplar Face Detection,
ICCV15(1994-2002)
IEEE DOI
1602
Databases
BibRef
Booth, J.[James],
Roussos, A.[Anastasios],
Ververas, E.[Evangelos],
Antonakos, E.[Epameinondas],
Ploumpis, S.[Stylianos],
Panagakis, Y.[Yannis],
Zafeiriou, S.P.[Stefanos P.],
3D Reconstruction of 'In-the-Wild' Faces in Images and Videos,
PAMI(40), No. 11, November 2018, pp. 2638-2652.
IEEE DOI
1810
Shape, Solid modeling,
Image reconstruction, Videos, Lighting, Benchmark testing, 3DMM,
3D reconstruction
BibRef
Booth, J.,
Antonakos, E.,
Ploumpis, S.,
Trigeorgis, G.,
Panagakis, Y.,
Zafeiriou, S.P.,
3D Face Morphable Models 'In-the-Wild',
CVPR17(5464-5473)
IEEE DOI
1711
Cameras, Data models, Face, Image reconstruction, Shape,
Solid modeling,
BibRef
Moschoglou, S.[Stylianos],
Ploumpis, S.[Stylianos],
Nicolaou, M.A.[Mihalis A.],
Zafeiriou, S.P.[Stefanos P.],
Multi-Attribute Probabilistic Linear Discriminant Analysis for 3D
Facial Shapes,
ACCV18(III:493-508).
Springer DOI
1906
BibRef
Sun, Y.C.[Yue-Chuan],
Yu, J.[Jun],
General-to-specific learning for facial attribute classification in
the wild,
JVCIR(56), 2018, pp. 83-91.
Elsevier DOI
1811
Facial attribute, Deep convolutional network, Joint learning,
Task-aware learning
BibRef
Masi, I.[Iacopo],
Chang, F.J.[Feng-Ju],
Choi, J.M.[Jong-Moo],
Harel, S.[Shai],
Kim, J.[Jung_Yeon],
Kim, K.[Kang_Geon],
Leksut, J.T.[Jatuporn T.],
Rawls, S.[Stephen],
Wu, Y.[Yue],
Hassner, T.[Tal],
Abd Almageed, W.[Wael],
Medioni, G.[Gerard],
Morency, L.P.[Louis-Philippe],
Natarajan, P.[Prem],
Nevatia, R.[Ram],
Learning Pose-Aware Models for Pose-Invariant Face Recognition in the
Wild,
PAMI(41), No. 2, February 2019, pp. 379-393.
IEEE DOI
1901
Face, Benchmark testing,
Face recognition, Training, Solid modeling,
pose-aware
BibRef
Masi, I.,
Rawls, S.,
Medioni, G.,
Natarajan, P.,
Pose-Aware Face Recognition in the Wild,
CVPR16(4838-4846)
IEEE DOI
1612
BibRef
Ge, S.M.[Shi-Ming],
Zhao, S.W.[Sheng-Wei],
Li, C.Y.[Chen-Yu],
Zhang, Y.[Yu],
Li, J.[Jia],
Efficient Low-Resolution Face Recognition via Bridge Distillation,
IP(29), 2020, pp. 6898-6908.
IEEE DOI
2007
BibRef
Earlier: A1, A2, A3, A5, Only:
Low-Resolution Face Recognition in the Wild via Selective Knowledge
Distillation,
IP(28), No. 4, April 2019, pp. 2051-2062.
IEEE DOI
1901
Face, Face recognition, Adaptation models, Image resolution,
Training, Computational modeling, Bridges,
CNNs
feedforward neural nets, image classification,
image resolution, learning (artificial intelligence),
CNNs
BibRef
Zhang, K.K.[Kang-Kai],
Ge, S.M.[Shi-Ming],
Shi, R.X.[Rui-Xin],
Zeng, D.[Dan],
Low-Resolution Object Recognition With Cross-Resolution Relational
Contrastive Distillation,
CirSysVideo(34), No. 4, April 2024, pp. 2374-2384.
IEEE DOI
2404
Face recognition, Object recognition, Knowledge transfer,
Adaptation models, Visualization, Training, Germanium,
domain adaptation
BibRef
Li, J.,
Liu, L.,
Li, J.,
Feng, J.,
Yan, S.,
Sim, T.,
Toward a Comprehensive Face Detector in the Wild,
CirSysVideo(29), No. 1, January 2019, pp. 104-114.
IEEE DOI
1901
Face, Face detection, Detectors, Training, Feature extraction,
Neural networks, Proposals, Bi-channel architecture, blur-aware,
video context
BibRef
Min, W.D.[Wei-Dong],
Fan, M.D.[Meng-Dan],
Li, J.[Jing],
Han, Q.[Qing],
Real-time face recognition based on pre-identification and multi-scale
classification,
IET-CV(13), No. 2, March 2019, pp. 165-171.
DOI Link
1902
Pedestrian scenes.
BibRef
Li, F.[Fei],
Jiang, M.Y.[Ming-Yan],
Low-resolution face recognition and feature selection based on
multidimensional scaling joint L 2,1-norm regularisation,
IET-Bio(8), No. 3, May 2019, pp. 198-205.
DOI Link
1904
BibRef
Gaston, J.,
Ming, J.,
Crookes, D.,
Matching Larger Image Areas for Unconstrained Face Identification,
Cyber(49), No. 8, August 2019, pp. 3191-3202.
IEEE DOI
1905
Training, Testing, Face, Training data, Lighting, Robustness,
Correlation, Block-based correlation, face identification,
patch-based image processing
BibRef
Wang, M.J.[Meng-Jiao],
Shu, Z.X.[Zhi-Xin],
Cheng, S.Y.[Shi-Yang],
Panagakis, Y.[Yannis],
Samaras, D.[Dimitris],
Zafeiriou, S.P.[Stefanos P.],
An Adversarial Neuro-Tensorial Approach for Learning Disentangled
Representations,
IJCV(127), No. 6-7, June 2019, pp. 743-762.
Springer DOI
1906
Disentangle pose, illumination and deformation.
BibRef
Zhang, H.,
Li, Q.,
Sun, Z.,
Adversarial Learning Semantic Volume for 2D/3D Face Shape Regression
in the Wild,
IP(28), No. 9, Sep. 2019, pp. 4526-4540.
IEEE DOI
1908
face recognition, image representation,
learning (artificial intelligence), neural nets,
auxiliary regression adversarial learning
BibRef
Ameur, B.[Bilel],
Belahcene, M.[Mebarka],
Masmoudi, S.[Sabeur],
Ben Hamida, A.[Ahmed],
Hybrid descriptors and Weighted PCA-EFMNet for Face Verification in the
Wild,
MultInfoRetr(8), No. 3, September 2019, pp. 143-154.
Springer DOI
1908
BibRef
Peng, Y.X.[Yu-Xi],
Spreeuwers, L.J.[Luuk J.],
Veldhuis, R.N.J.[Raymond N.J.],
Low-resolution face alignment and recognition using mixed-resolution
classifiers,
IET-Bio(6), No. 6, November 2017, pp. 418-428.
DOI Link
1711
BibRef
Peng, Y.X.[Yu-Xi],
Spreeuwers, L.J.[Luuk J.],
Veldhuis, R.N.J.[Raymond N.J.],
Low-resolution face recognition and the importance of proper alignment,
IET-Bio(8), No. 4, July 2019, pp. 267-276.
DOI Link
1906
BibRef
Zeng, D.[Dan],
Spreeuwers, L.J.[Luuk J.],
Veldhuis, R.N.J.[Raymond N.J.],
Zhao, Q.J.[Qi-Jun],
Combined training strategy for low-resolution face recognition with
limited application-specific data,
IET-IPR(13), No. 10, 22 August 2019, pp. 1790-1796.
DOI Link
1909
BibRef
Ke, X.[Xiao],
Li, J.P.[Jian-Ping],
Guo, W.Z.[Wen-Zhong],
Dense small face detection based on regional cascade multi-scale method,
IET-IPR(13), No. 14, 12 December 2019, pp. 2796-2804.
DOI Link
1912
BibRef
Ly, T.S.[Thai Son],
Do, N.T.[Nhu-Tai],
Kim, S.H.[Soo-Hyung],
Yang, H.J.[Hyung-Jeong],
Lee, G.S.[Guee-Sang],
A novel 2D and 3D multimodal approach for in-the-wild facial
expression recognition,
IVC(92), 2019, pp. 103817.
Elsevier DOI
1912
Facial expression recognition, In-the-wild FER, 2D + 3D FER
BibRef
Sun, J.N.[Jing-Na],
Shen, Y.[Yehu],
Yang, W.M.[Wen-Ming],
Liao, Q.M.[Qing-Min],
Classifier shared deep network with multi-hierarchy loss for low
resolution face recognition,
SP:IC(82), 2020, pp. 115766.
Elsevier DOI
2001
Low-resolution face recognition,
Classifier shared deep network, Multi-hierarchy loss, Intermediate features
BibRef
Mu, G.D.[Guo-Dong],
Huang, D.[Di],
Hu, G.S.[Guo-Sheng],
Sun, J.[Jia],
Wang, Y.H.[Yun-Hong],
Led3D: A Lightweight and Efficient Deep Approach to Recognizing
Low-Quality 3D Faces,
CVPR19(5766-5775).
IEEE DOI
2002
BibRef
Hong, S.,
Ryu, J.,
Unsupervised Face Domain Transfer for Low-Resolution Face Recognition,
SPLetters(27), 2020, pp. 156-160.
IEEE DOI
2002
Low-resolution face recognition, image-to-image translation,
domain adaptation, attention, face augmentation
BibRef
Sikkandar, H.[Haseena],
Thiyagarajan, R.[Revathi],
Soft biometrics-based face image retrieval using improved Grey Wolf
Optimisation,
IET-IPR(14), No. 3, 28 February 2020, pp. 451-461.
DOI Link
2002
Unconstrained images.
BibRef
Gundogdu, B.[Batuhan],
Bianco, M.J.[Michael J.],
Collaborative similarity metric learning for face recognition in the
wild,
IET-IPR(14), No. 9, 20 July 2020, pp. 1759-1768.
DOI Link
2007
BibRef
Cheng, Z.Y.[Zhi-Yi],
Zhu, X.T.[Xia-Tian],
Gong, S.G.[Shao-Gang],
Face re-identification challenge:
Are face recognition models good enough?,
PR(107), 2020, pp. 107422.
Elsevier DOI
2008
Face re-identification, Surveillance facial imagery,
Low-resolution, Super-resolution, Open-set matching, Face recognition
BibRef
Xi, Y.[Yue],
Zheng, J.B.[Jiang-Bin],
He, X.J.[Xiang-Jian],
Jia, W.J.[Wen-Jing],
Li, H.H.[Han-Hui],
Xie, Y.F.[Ye-Fan],
Feng, M.C.[Ming-Chen],
Li, X.X.[Xiu-Xiu],
Beyond context: Exploring semantic similarity for small object
detection in crowded scenes,
PRL(137), 2020, pp. 53-60.
Elsevier DOI
2008
BibRef
Earlier: A1, A2, A3, A4, A5, Only:
Beyond Context: Exploring Semantic Similarity for Tiny Face Detection,
ICIP18(1907-1911)
IEEE DOI
1809
Face, Face detection, Semantics, Measurement, Detectors,
Feature extraction, Computer science, Tiny face detection,
graph-cut
BibRef
Ge, S.,
Li, C.,
Zhao, S.,
Zeng, D.,
Occluded Face Recognition in the Wild by Identity-Diversity
Inpainting,
CirSysVideo(30), No. 10, October 2020, pp. 3387-3397.
IEEE DOI
2010
Face, Face recognition,
Generative adversarial networks, Feature extraction,
deep learning
BibRef
Low, C.Y.,
Teoh, A.B.J.,
Park, J.,
MIND-Net: A Deep Mutual Information Distillation Network for
Realistic Low-Resolution Face Recognition,
SPLetters(28), 2021, pp. 354-358.
IEEE DOI
2102
Face recognition, Training, Task analysis, Mutual information,
Probes, Streaming media, Feature extraction,
mutual information distillation
BibRef
Rouhsedaghat, M.[Mozhdeh],
Wang, Y.F.[Yi-Fan],
Hu, S.[Shuowen],
You, S.[Suya],
Kuo, C.C.J.[C.C. Jay],
Low-resolution face recognition in resource-constrained environments,
PRL(149), 2021, pp. 193-199.
Elsevier DOI
2108
Low-resolution face recognition, Small model, Small data, SSL, Pixelhop++
BibRef
Liu, Y.F.[Yan-Fei],
Chen, J.H.[Jun-Hua],
Multi-factor joint normalisation for face recognition in the wild,
IET-CV(15), No. 6, 2021, pp. 405-417.
DOI Link
2108
BibRef
Jiao, Q.F.[Qian-Fen],
Li, R.[Rui],
Cao, W.M.[Wen-Ming],
Zhong, J.[Jian],
Wu, S.[Si],
Wong, H.S.[Hau-San],
DDAT: Dual domain adaptive translation for low-resolution face
verification in the wild,
PR(120), 2021, pp. 108107.
Elsevier DOI
2109
Low-resolution face verification, Domain adaptation,
Image translation, GAN
BibRef
Mishra, N.K.[Nayaneesh Kumar],
Dutta, M.[Mainak],
Singh, S.K.[Satish Kumar],
Multiscale parallel deep CNN (mpdCNN) architecture for the real
low-resolution face recognition for surveillance,
IVC(115), 2021, pp. 104290.
Elsevier DOI
2110
Face recognition, Low-resolution images, Surveillance,
Multiscale parallel architecture, Convolution neural network
BibRef
Mishra, N.K.[Nayaneesh Kumar],
Singh, S.K.[Satish Kumar],
Regularized Hardmining loss for face recognition,
IVC(117), 2022, pp. 104343.
Elsevier DOI
2112
Face Recognition, Hardmining loss, Regularized Hardmining loss
BibRef
Zhang, Z.Y.[Zi-Yu],
Da, F.[Feipeng],
Yu, Y.[Yi],
Learning directly from synthetic point clouds for 'in-the-wild' 3D
face recognition,
PR(123), 2022, pp. 108394.
Elsevier DOI
2112
3D face recognition, Learning from synthetic,
Curvature-aware point sampling, Transfer learning
BibRef
Horng, S.J.[Shi-Jinn],
Supardi, J.[Julian],
Zhou, W.[Wanlei],
Lin, C.T.[Chin-Teng],
Jiang, B.[Bin],
Recognizing Very Small Face Images Using Convolution Neural Networks,
ITS(23), No. 3, March 2022, pp. 2103-2115.
IEEE DOI
2203
Face recognition, Image recognition, Convolution, Databases,
Image reconstruction, Very low resolution, residual learning
BibRef
Liang, J.X.[Jin-Xiu],
Wang, J.W.[Jing-Wen],
Quan, Y.H.[Yu-Hui],
Chen, T.Y.[Tian-Yi],
Liu, J.Y.[Jia-Ying],
Ling, H.B.[Hai-Bin],
Xu, Y.[Yong],
Recurrent Exposure Generation for Low-Light Face Detection,
MultMed(24), 2022, pp. 1609-1621.
IEEE DOI
2204
Face detection, Faces, Lighting, Detectors, Face recognition,
Task analysis, Benchmark testing, Gated recurrent networks, multi-exposure
BibRef
Singh, M.[Maneet],
Nagpal, S.[Shruti],
Singh, R.[Richa],
Vatsa, M.[Mayank],
DeriveNet for (Very) Low Resolution Image Classification,
PAMI(44), No. 10, October 2022, pp. 6569-6577.
IEEE DOI
2209
BibRef
Earlier:
Dual Directed Capsule Network for Very Low Resolution Image
Recognition,
ICCV19(340-349)
IEEE DOI
2004
Face recognition, Image resolution, Feature extraction,
Image reconstruction, Training, Task analysis, Image recognition,
digit classification.
cameras, image sensors.
BibRef
Zhao, P.Z.[Pan-Zi],
Ming, Y.[Yue],
Meng, X.Y.[Xu-Yang],
Yu, H.[Hui],
LMFNet: A Lightweight Multiscale Fusion Network With Hierarchical
Structure for Low-Quality 3-D Face Recognition,
HMS(53), No. 1, February 2023, pp. 239-252.
IEEE DOI
2301
Face recognition, Feature extraction, Real-time systems,
Solid modeling, Robustness, Convolutional neural networks, real-time
BibRef
Zhang, P.N.[Pu-Ning],
Huang, F.Y.[Feng-Yi],
Wu, D.P.[Da-Peng],
Yang, B.[Boran],
Yang, Z.G.[Zhi-Gang],
Tan, L.[Lei],
Device-Edge-Cloud Collaborative Acceleration Method Towards Occluded
Face Recognition in High-Traffic Areas,
MultMed(25), 2023, pp. 1513-1520.
IEEE DOI
2305
Face recognition, Feature extraction, Computational modeling,
Collaboration, Image edge detection, Delays, Servers, model partitioning
BibRef
Qian, J.J.[Jian-Jun],
Zhu, S.[Shumin],
Zhao, C.[Chaoyu],
Yang, J.[Jian],
Wong, W.K.[Wai Keung],
OTFace: Hard Samples Guided Optimal Transport Loss for Deep Face
Representation,
MultMed(25), 2023, pp. 1427-1438.
IEEE DOI
2305
Face recognition, Training, Task analysis, Neural networks,
Facial features, Representation learning, Generators,
Optimal transport
BibRef
Parres, D.[Daniel],
Paredes, R.[Roberto],
Lightweight Vision Transformers for Face Verification in the Wild,
IbPRIA23(414-425).
Springer DOI
2307
BibRef
Zhou, W.T.[Wen-Tao],
Zhang, Y.S.[Yu-Shu],
Zhao, R.[Ruoyu],
Yi, S.[Shuang],
Lan, R.[Rushi],
Adversarial Thumbnail-Preserving Transformation for Facial Images
Based on GAN,
SPLetters(30), 2023, pp. 1147-1151.
IEEE DOI
2310
BibRef
Xu, R.Z.[Rui-Zhuo],
Wang, K.[Ke],
Deng, C.[Chao],
Wang, M.[Mei],
Chen, X.[Xi],
Huang, W.H.[Wen-Hui],
Feng, J.[Junlan],
Deng, W.H.[Wei-Hong],
Depth Map Denoising Network and Lightweight Fusion Network for
Enhanced 3D Face Recognition,
PR(145), 2024, pp. 109936.
Elsevier DOI
2311
Depth map denoising, Implicit neural representations,
Low-quality 3D face recognition, Lightweight network, Deep learning
BibRef
Zhang, K.B.[Kai-Bing],
Zheng, D.D.[Dong-Dong],
Li, J.[Jie],
Gao, X.B.[Xin-Bo],
Lu, J.[Jian],
Coupled discriminative manifold alignment for low-resolution face
recognition,
PR(147), 2024, pp. 110049.
Elsevier DOI
2312
Low-resolution face recognition, Discriminative manifold embedding,
Feature subspace
BibRef
Zhang, M.[Meng],
Liu, R.J.[Ru-Jie],
Deguchi, D.[Daisuke],
Murase, H.[Hiroshi],
Texture-Guided Transfer Learning for Low-Quality Face Recognition,
IP(33), 2024, pp. 95-107.
IEEE DOI
2312
BibRef
Ding, X.[Xin],
Wang, Z.[Zheng],
Fang, J.[Jing],
Shu, Z.Y.[Zhen-Yu],
Hu, R.M.[Rui-Min],
Lin, C.W.[Chia-Wen],
Watch You Under Low-Resolution and Low-Illumination:
Face Enhancement via Bi-Factor Degradation Decoupling,
CirSysVideo(34), No. 5, May 2024, pp. 3481-3495.
IEEE DOI
2405
Faces, Degradation, Image reconstruction, Lighting, Image resolution,
Brightness, Kernel, Degradation analysis, super-resolution, VAE
BibRef
Chen, C.[Can],
McCloskey, S.[Scott],
High-Resolution Image Enumeration for Low-Resolution Face Recognition,
FG24(1-9)
IEEE DOI
2408
Uncertainty, Image resolution, Image recognition, Face recognition,
Gesture recognition, Image enhancement
BibRef
Zhu, H.D.[Hai-Dong],
Zheng, W.[Wanrong],
Zheng, Z.H.[Zhao-Heng],
Nevatia, R.[Ram],
ShARc: Shape and Appearance Recognition for Person Identification
In-the-wild,
WACV24(6278-6288)
IEEE DOI
2404
Degradation, Shape, Biometrics (access control),
Feature extraction, Skeleton, Data mining, Algorithms, Biometrics,
Video recognition and understanding
BibRef
Chai, J.C.L.[Jacky Chen Long],
Ng, T.S.[Tiong-Sik],
Low, C.Y.[Cheng-Yaw],
Park, J.[Jaewoo],
Teoh, A.B.J.[Andrew Beng Jin],
Recognizability Embedding Enhancement for Very Low-Resolution Face
Recognition and Quality Estimation,
CVPR23(9957-9967)
IEEE DOI
2309
BibRef
Shin, S.[Sungho],
Lee, J.[Joosoon],
Lee, J.[Junseok],
Yu, Y.[Yeonguk],
Lee, K.[Kyoobin],
Teaching Where to Look: Attention Similarity Knowledge Distillation for
Low Resolution Face Recognition,
ECCV22(XII:631-647).
Springer DOI
2211
BibRef
Teng, W.B.[Wen-Bin],
Bai, C.Y.[Chong-Yang],
Unimodal Face Classification with Multimodal Training,
FG21(1-5)
IEEE DOI
2303
Training, Adaptation models, Sentiment analysis,
Face recognition, Sensors, Task analysis
BibRef
Fang, H.[Han],
Deng, W.H.[Wei-Hong],
Zhong, Y.Y.[Yao-Yao],
Hu, J.[Jiani],
Zhao, D.Y.[Dong-Yue],
Li, X.[Xian],
Wen, D.C.[Dong-Chao],
Augmented Face Representation Learning via Transitive Distillation,
FG21(1-8)
IEEE DOI
2303
Representation learning, Bridges, Face recognition, Benchmark testing
BibRef
Geng, Q.X.[Qi-Xiang],
Liang, D.[Dong],
Zhou, H.Y.[Hui-Yu],
Zhang, L.Y.[Li-Yan],
Sun, H.[Han],
Liu, N.Z.[Ning-Zhong],
Dense Face Detection via High-level Context Mining,
FG21(1-8)
IEEE DOI
2303
Training, Degradation, Face recognition, Detectors, Benchmark testing
BibRef
Wang, H.H.[Hai-Han],
Wang, S.F.[Shang-Fei],
Low-Resolution Face Recognition Enhanced by High-Resolution Facial
Images,
FG23(1-8)
IEEE DOI
2303
Training, Visualization, Image resolution, Image recognition, Shape,
Face recognition, Benchmark testing
BibRef
Filho, H.P.[Helio Perroni],
Trajcevski, A.[Aleksander],
Bhargava, K.[Kartikeya],
Javed, N.[Nizwa],
Elder, J.H.[James H.],
Attentive Sensing for Long-Range Face Recognition,
LongRange23(613-622)
IEEE DOI
2302
Visualization, Face recognition, Conferences, Social robots,
Robot vision systems, Cameras
BibRef
Cornett, D.[David],
Brogan, J.[Joel],
Barber, N.[Nell],
Aykac, D.[Deniz],
Baird, S.[Seth],
Burchfield, N.[Nick],
Dukes, C.[Carl],
Duncan, A.[Andrew],
Ferrell, R.[Regina],
Goddard, J.[Jim],
Jager, G.[Gavin],
Larson, M.[Matt],
Murphy, B.[Bart],
Johnson, C.[Christi],
Shelley, I.[Ian],
Srinivas, N.[Nisha],
Stockwell, B.[Brandon],
Thompson, L.[Leanne],
Yohe, M.[Matt],
Zhang, R.[Robert],
Dolvin, S.[Scott],
Santos-Villalobos, H.J.[Hector J.],
Bolme, D.S.[David S.],
Expanding Accurate Person Recognition to New Altitudes and Ranges:
The BRIAR Dataset,
LongRange23(593-602)
IEEE DOI
2302
Training, Deep learning, Image resolution,
Social networking (online), Face recognition, Surveillance, Forensics
BibRef
Kocabas, M.[Muhammed],
Huang, C.H.P.[Chun-Hao P.],
Tesch, J.[Joachim],
Müller, L.[Lea],
Hilliges, O.[Otmar],
Black, M.J.[Michael J.],
SPEC: Seeing People in the Wild with an Estimated Camera,
ICCV21(11015-11025)
IEEE DOI
2203
Geometry, Shape, Neural networks, Estimation, Cameras,
Gestures and body pose, 3D from a single image and shape-from-x
BibRef
Wood, E.[Erroll],
Baltrušaitis, T.[Tadas],
Hewitt, C.[Charlie],
Dziadzio, S.[Sebastian],
Cashman, T.J.[Thomas J.],
Shotton, J.[Jamie],
Fake it till you make it: face analysis in the wild using synthetic
data alone,
ICCV21(3661-3671)
IEEE DOI
2203
Training, Adaptation models, Solid modeling, Training data, Manuals,
Faces, Datasets and evaluation,
grouping and shape
BibRef
Abed, R.[Rahma],
Bahroun, S.[Sahbi],
Zagrouba, E.[Ezzeddine],
Toward a Robust Shape and Texture Face Descriptor for Efficient Face
Recognition in the Wild,
CAIP21(II:319-328).
Springer DOI
2112
BibRef
Yu, J.[Jun],
Hao, X.L.[Xin-Long],
He, P.[Peng],
Single-stage Face Detection under Extremely Low-light Conditions,
RLQ21(3516-3525)
IEEE DOI
2112
Image quality, Image color analysis, Design methodology,
Brightness, Feature extraction, Face detection
BibRef
Zhang, Z.Y.[Zhen-Yu],
Ge, Y.[Yanhao],
Chen, R.[Renwang],
Tai, Y.[Ying],
Yan, Y.[Yan],
Yang, J.[Jian],
Wang, C.J.[Cheng-Jie],
Li, J.L.[Ji-Lin],
Huang, F.Y.[Fei-Yue],
Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo
Collection,
CVPR21(14209-14219)
IEEE DOI
2111
Solid modeling, Adaptation models,
Image resolution, Shape, Image color analysis, Face recognition
BibRef
Li, B.[Bi],
Xi, T.[Teng],
Zhang, G.[Gang],
Feng, H.C.[Hao-Cheng],
Han, J.Y.[Jun-Yu],
Liu, J.[Jingtuo],
Ding, E.[Errui],
Liu, W.Y.[Wen-Yu],
Dynamic Class Queue for Large Scale Face Recognition In the Wild,
CVPR21(3762-3771)
IEEE DOI
2111
Training, Deep learning, Costs, Codes,
Face recognition, Computational modeling
BibRef
Wang, H.R.[Han-Rui],
Dong, X.B.[Xing-Bo],
Jin, Z.[Zhe],
Dugelay, J.L.[Jean-Luc],
Tistarelli, M.[Massimo],
Cross-spectrum Face Recognition Using Subspace Projection Hashing,
ICPR21(615-622)
IEEE DOI
2105
Deep learning, Face recognition,
Information services, Benchmark testing, Internet, Task analysis,
subspace projection hashing
BibRef
Martínez-Díaz, Y.[Yoanna],
Méndez-Vázquez, H.[Heydi],
Luevano, L.S.[Luis S.],
Chang, L.[Leonardo],
Gonzalez-Mendoza, M.[Miguel],
Lightweight Low-Resolution Face Recognition for Surveillance
Applications,
ICPR21(5421-5428)
IEEE DOI
2105
Training, Image quality, Image recognition, Face recognition,
Computational modeling, Surveillance, Benchmark testing
BibRef
Ferreira, C.B.R.[Cristiane B. R.],
Pedrini, H.[Helio],
de Souza Alencar, W.[Wanderley],
Ferreira, W.D.[William D.],
Carvalho, T.P.[Thyago Peres],
Sousa, N.[Naiane],
Soares, F.[Fabrizzio],
Where's Wally: A Gigapixel Image Study for Face Recognition in Crowds,
ISVC20(II:386-397).
Springer DOI
2103
BibRef
Bianco, S.[Simone],
Celona, L.[Luigi],
Schettini, R.[Raimondo],
Who Is in the Crowd? Deep Face Analysis for Crowd Understanding,
DEEPRETAIL20(487-494).
Springer DOI
2103
BibRef
Han, X.,
Ji, Z.,
Wang, W.,
Low Resolution Facial Manipulation Detection,
VCIP20(431-434)
IEEE DOI
2102
Feature extraction, Image resolution, Videos, Degradation,
Data mining, Signal resolution, Faces, Manipulation Detection,
Key points-based Fusion Pooling
BibRef
Roy Chowdhury, A.[Aruni],
Yu, X.[Xiang],
Sohn, K.[Kihyuk],
Learned-Miller, E.G.[Erik G.],
Chandraker, M.[Manmohan],
Improving Face Recognition by Clustering Unlabeled Faces in the Wild,
ECCV20(XXIV:119-136).
Springer DOI
2012
BibRef
Fang, H.[Han],
Deng, W.H.[Wei-Hong],
Zhong, Y.Y.[Yao-Yao],
Hu, J.[Jiani],
Generate to Adapt:
Resolution Adaption Network for Surveillance Face Recognition,
ECCV20(XV:741-758).
Springer DOI
2011
BibRef
Wu, Y.,
Wu, Y.,
Gong, R.,
Lv, Y.,
Chen, K.,
Liang, D.,
Hu, X.,
Liu, X.,
Yan, J.,
Rotation Consistent Margin Loss for Efficient Low-Bit Face
Recognition,
CVPR20(6865-6875)
IEEE DOI
2008
Quantization (signal), Protocols, Task analysis, Face, Training,
Face recognition, Acceleration
BibRef
Zhong, Y.,
Wang, X.,
Zhang, S.,
Robust Partial Matching for Person Search in the Wild,
CVPR20(6826-6834)
IEEE DOI
2008
Feature extraction, Detectors, Robustness, Training, Body regions,
Noise measurement, Task analysis
BibRef
Zhang, Z.S.[Zhi-Shuai],
Shen, W.[Wei],
Qiao, S.Y.[Si-Yuan],
Wang, Y.[Yan],
Wang, B.[Bo],
Yuille, A.L.[Alan L.],
Robust Face Detection via Learning Small Faces on Hard Images,
WACV20(1350-1359)
IEEE DOI
2006
Face, Detectors, Feature extraction, Training, Face detection, Robustness
BibRef
Yu, X.,
Gong, Y.,
Jiang, N.,
Ye, Q.,
Han, Z.,
Scale Match for Tiny Person Detection,
WACV20(1246-1254)
IEEE DOI
2006
Detectors, Benchmark testing, Object detection, Face, Earth,
Convolutional neural networks, Feature extraction
BibRef
Mynepalli, S.C.,
Hu, P.,
Ramanan, D.,
Recognizing Tiny Faces,
RLQ19(1121-1130)
IEEE DOI
2004
face recognition, feature extraction, image representation,
image resolution, object recognition, tiny faces, continuous range,
Deep learning
BibRef
Gong, S.,
Shi, Y.,
Jain, A.,
Low Quality Video Face Recognition: Multi-Mode Aggregation Recurrent
Network (MARN),
RLQ19(1027-1035)
IEEE DOI
2004
face recognition, image sequences,
learning (artificial intelligence), recurrent neural nets,
Recurrent neural network
BibRef
Subramaniam, A.,
Sridhar, A.N.,
Mittal, A.,
Feature Ensemble Networks with Re-Ranking for Recognizing Disguised
Faces in the Wild,
DFW19(532-541)
IEEE DOI
2004
face recognition, feature extraction, learning (artificial intelligence),
BibRef
Singh, M.,
Chawla, M.,
Singh, R.,
Vatsa, M.,
Chellappa, R.,
Disguised Faces in the Wild 2019,
DFW19(542-550)
IEEE DOI
2004
face recognition, learning (artificial intelligence),
disguise variations, Wild 2019 competition, DFW2019 dataset,
Disguised Face Recognition
BibRef
Ming, X.[Xiang],
Wei, F.Y.[Fang-Yun],
Zhang, T.[Ting],
Chen, D.[Dong],
Zheng, N.N.[Nan-Ning],
Wen, F.[Fang],
Group Sampling for Scale Invariant Face Detection,
PAMI(44), No. 2, February 2022, pp. 985-1001.
IEEE DOI
2201
BibRef
Earlier: A1, A2, A3, A4, A6, Only:
CVPR19(3441-3451).
IEEE DOI
2002
Feature extraction, Training, Face, Detectors, Face detection,
Network architecture, Object detection, sampling.
BibRef
Yudin, D.,
Ivanov, A.,
Shchendrygin, M.,
Detection of a Human Head On a Low-quality Image and Its Software
Implementation,
PTVSBB19(237-241).
DOI Link
1912
BibRef
Massoli, F.V.[Fabio Valerio],
Amato, G.[Giuseppe],
Falchi, F.[Fabrizio],
Gennaro, C.[Claudio],
Vairo, C.[Claudio],
Improving Multi-scale Face Recognition Using VGGFace2,
NTIAP19(21-29).
Springer DOI
1909
BibRef
Carrara, F.[Fabio],
Amato, G.[Giuseppe],
Falchi, F.[Fabrizio],
Gennaro, C.[Claudio],
Evaluation of Continuous Image Features Learned by ODE Nets,
CIAP19(I:432-442).
Springer DOI
1909
BibRef
Das, A.[Apurba],
Saha, P.[Pallavi],
Enhancing Low Quality Face Image Matching by Neurovisually Inspired
Deep Learning,
CAIP19(II:544-555).
Springer DOI
1909
BibRef
Cheng, Z.Y.[Zhi-Yi],
Zhu, X.T.[Xia-Tian],
Gong, S.G.[Shao-Gang],
Low-Resolution Face Recognition,
ACCV18(III:605-621).
Springer DOI
1906
BibRef
Mudunuri, S.P.,
Sanyal, S.,
Biswas, S.,
GenLR-Net: Deep Framework for Very Low Resolution Face and Object
Recognition with Generalization to Unseen Categories,
Biometrics18(602-60209)
IEEE DOI
1812
Image resolution, Face, Training, Object recognition, Databases,
Testing, Task analysis
BibRef
Yuan, Y.,
Zhang, Z.,
Li, Y.,
Qiang, J.,
Li, B.,
Shen, X.,
Learning Parallel Canonical Correlations for Scale-Adaptive Low
Resolution Face Recognition,
ICPR18(922-927)
IEEE DOI
1812
Face, Face recognition, Image resolution, Correlation,
Image reconstruction, Training, Transforms, face recognition,
multiple resolutions
BibRef
Peri, S.V.,
Dhall, A.,
DisguiseNet: A Contrastive Approach for Disguised Face Verification
in the Wild,
DFW18(25-256)
IEEE DOI
1812
Face, Task analysis, Face recognition, Feature extraction,
Visualization, Training, Noise measurement
BibRef
Kushwaha, V.,
Singh, M.,
Singh, R.,
Vatsa, M.,
Ratha, N.,
Chellappa, R.,
Disguised Faces in the Wild,
DFW18(1-18)
IEEE DOI
1812
Pattern recognition
BibRef
Bansal, A.,
Ranjan, R.,
Castillo, C.D.,
Chellappa, R.,
Deep Features for Recognizing Disguised Faces in the Wild,
DFW18(10-106)
IEEE DOI
1812
Training, Face recognition, Pipelines, Measurement,
Face detection, Feature extraction
BibRef
Zhu, C.,
Tao, R.,
Luu, K.,
Savvides, M.,
Seeing Small Faces from Robust Anchor's Perspective,
CVPR18(5127-5136)
IEEE DOI
1812
Detectors, Face detection, Training, Feature extraction,
Network architecture, Image color analysis, Lapping
BibRef
Zhao, J.,
Cheng, Y.,
Xu, Y.,
Xiong, L.,
Li, J.,
Zhao, F.,
Jayashree, K.,
Pranata, S.,
Shen, S.,
Xing, J.,
Yan, S.,
Feng, J.,
Towards Pose Invariant Face Recognition in the Wild,
CVPR18(2207-2216)
IEEE DOI
1812
Face, Face recognition, Training, Generators,
Optimization, Benchmark testing
BibRef
Guo, B.H.,
Nixon, M.S.,
Carter, J.N.,
A Joint Density Based Rank-Score Fusion for Soft Biometric
Recognition at a Distance,
ICPR18(3457-3462)
IEEE DOI
1812
Face, Clothing, Face recognition, Databases, Shape, Cameras, Skin,
Soft biometric, recognition at different distances, rank-score fusion
BibRef
Gonzalez-Sosa, E.,
Vera-Rodriguez, R.,
Hernandez-Ortega, J.,
Fierrez, J.,
Person Recognition at a Distance:
Improving Face Recognition Through Body Static Information,
ICPR18(3439-3444)
IEEE DOI
1812
Face, Feature extraction, Face recognition, Shape, Data mining, Databases
BibRef
Jiang, F.[Feng],
Zhang, J.[Jie],
Yan, L.P.[Li-Ping],
Xia, Y.Q.[Yuan-Qing],
Shan, S.G.[Shi-Guang],
A Three-Category Face Detector with Contextual Information on Finding
Tiny Faces,
ICIP18(2680-2684)
IEEE DOI
1809
Face, Detectors, Face detection, Proposals, Training, Task analysis,
Face recognition, Three-category classification, face detector,
contextual information
BibRef
Zhou, Y.,
Liu, D.,
Huang, T.,
Survey of Face Detection on Low-Quality Images,
FG18(769-773)
IEEE DOI
1806
Detectors, Face, Face detection, Feature extraction,
Machine learning, Robustness, Testing, Face Detection, Low-quality
BibRef
Samangouei, P.,
Chellappa, R.,
Najibi, M.,
Davis, L.S.,
Face-MagNet: Magnifying Feature Maps to Detect Small Faces,
WACV18(122-130)
IEEE DOI
1806
convolution, deconvolution, face recognition,
feedforward neural nets, image classification, object detection,
Proposals
BibRef
Liu, Y.G.[Yu-Guang],
Levine, M.D.[Martin D.],
Multi-path Region-Based Convolutional Neural Network for Accurate
Detection of Unconstrained 'Hard Faces',
CRV17(183-190)
IEEE DOI
1804
Very small. (Far?)
convolution, face recognition, feedforward neural nets,
image fusion, learning (artificial intelligence),
tiny faces
BibRef
Kankanamge, S.,
Fookes, C.,
Sridharan, S.,
Facial analysis in the wild with LSTM networks,
ICIP17(1052-1056)
IEEE DOI
1803
Analytical models, Computational modeling, Computer architecture,
Databases, Face recognition, Feature extraction, Training, ExpModel,
LSTM
BibRef
Hu, P.,
Ramanan, D.,
Finding Tiny Faces,
CVPR17(1522-1530)
IEEE DOI
1711
Context modeling, Detectors, Face recognition, Feature extraction,
Image recognition, Image resolution, Training
BibRef
Bai, Y.C.[Yan-Cheng],
Ma, W.J.[Wen-Jing],
Li, Y.C.[Yu-Cheng],
Cao, L.L.[Liang-Liang],
Guo, W.[Wen],
Yang, L.[Luwei],
Multi-Scale Fully Convolutional Network for Fast Face Detection,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Bai, Y.C.[Yan-Cheng],
Ghanem, B.[Bernard],
Multi-scale Fully Convolutional Network for Face Detection in the
Wild,
FaceWild17(2078-2087)
IEEE DOI
1709
Computer architecture, Detectors, Face, Face detection,
Feature extraction, Proposals, Training
BibRef
Marcetic, D.[Darijan],
Soldic, M.[Martin],
Ribaric, S.[Slobodan],
Hybrid Cascade Model for Face Detection in the Wild Based on Normalized
Pixel Difference and a Deep Convolutional Neural Network,
CAIP17(II: 379-390).
Springer DOI
1708
BibRef
Wang, Y.[Ya],
Bao, T.L.[Tian-Long],
Ding, C.H.[Chun-Hui],
Zhu, M.[Ming],
Face recognition in real-world surveillance videos with deep learning
method,
ICIVC17(239-243)
IEEE DOI
1708
Face, Face detection, Face recognition, Feature extraction,
Machine learning, Surveillance, Videos, deep learning,
face recognition, surveillance
BibRef
Li, J.J.[Jun-Jie],
Karmoshi, S.,
Zhu, M.[Ming],
Unconstrained Face Detection Based on Cascaded Convolutional Neural
Networks in Surveillance Video,
ICIVC17(46-52)
IEEE DOI
1708
Databases, Face, Face detection, Feature extraction,
Image color analysis, Skin, Surveillance, cascade classifier,
convolutional neural network, surveillance video, unconstrained,
Face, detection
BibRef
Obara, K.,
Yoshimura, H.,
Nishiyama, M.,
Iwai, Y.,
Low-resolution person recognition using image downsampling,
MVA17(478-481)
DOI Link
1708
Cameras, Face recognition, Feature extraction, Image resolution,
Mathematical model, Organizations
BibRef
Haghighat, M.[Mohammad],
Abdel-Mottaleb, M.[Mohamed],
Lower Resolution Face Recognition in Surveillance Systems Using
Discriminant Correlation Analysis,
FG17(912-917)
IEEE DOI
1707
Correlation, Covariance matrices, Face, Face recognition,
Image resolution, Probes, Surveillance
BibRef
Marras, I.[Ioannis],
Nikitidis, S.[Symeon],
Zafeiriou, S.P.[Stefanos P.],
Pantic, M.[Maja],
A Joint Discriminative Generative Model for Deformable Model
Construction and Classification,
FG17(127-134)
IEEE DOI
1707
Algorithm design and analysis, Computational modeling,
Deformable models, Face, Feature extraction, Optimization, Shape
BibRef
Yang, S.,
Wiliem, A.,
Lovell, B.C.,
To face or not to face: Towards reducing false positive of face
detection,
ICVNZ16(1-6)
IEEE DOI
1701
Benchmark testing
BibRef
San, W.Y.K.,
Chen, S.K.[Shao-Kang],
Wiliem, A.,
Di, B.,
Lovell, B.C.[Brian C.],
How do you develop a face detector for the unconstrained environment?,
ICVNZ16(1-6)
IEEE DOI
1701
Benchmark testing
BibRef
Zhong, Y.,
Sullivan, J.,
Li, H.,
Transferring from face recognition to face attribute prediction
through adaptive selection of off-the-shelf CNN representations,
ICPR16(2264-2269)
IEEE DOI
1705
BibRef
Earlier:
Leveraging mid-level deep representations for predicting face
attributes in the wild,
ICIP16(3239-3243)
IEEE DOI
1610
Error analysis, Face, Face recognition, Feature extraction, Mouth, Training.
BibRef
Verma, S.,
Mittal, P.,
Vatsa, M.,
Singh, R.,
At-a-distance person recognition via combining ocular features,
ICIP16(3131-3135)
IEEE DOI
1610
Databases
BibRef
Sengupta, S.,
Chen, J.C.[Jun-Cheng],
Castillo, C.,
Patel, V.M.[Vishal M.],
Chellappa, R.[Rama],
Jacobs, D.W.,
Frontal to profile face verification in the wild,
WACV16(1-9)
IEEE DOI
1606
Face
BibRef
Santhanam, V.,
Morariu, V.I.[Vlad I.],
Davis, L.S.[Larry S.],
Generalized Deep Image to Image Regression,
CVPR17(5395-5405)
IEEE DOI
1711
Computer architecture, Convolution, Face, Feature extraction,
Image color analysis, Noise, reduction
BibRef
Li, A.[Ang],
Morariu, V.I.[Vlad I.],
Davis, L.S.[Larry S.],
Selective Encoding for Recognizing Unreliably Localized Faces,
ICCV15(3613-3621)
IEEE DOI
1602
Authentication
BibRef
Burgos-Artizzu, X.P.[Xavier P.],
Zepeda, J.,
Clerc, F.L.,
Perez, P.,
Pose and Expression-Coherent Face Recovery in the Wild,
RSL-CV15(877-885)
IEEE DOI
1602
Dictionaries;Encoding;Estimation;Face;Shape;Training
BibRef
Zhu, X.Y.[Xiang-Yu],
Lei, Z.[Zhen],
Yan, J.J.[Jun-Jie],
Yi, D.[Dong],
Li, S.Z.[Stan Z.],
High-fidelity Pose and Expression Normalization for face recognition
in the wild,
CVPR15(787-796)
IEEE DOI
1510
BibRef
Yang, B.[Bin],
Yan, J.J.[Jun-Jie],
Lei, Z.[Zhen],
Li, S.Z.,
Fine-grained evaluation on face detection in the wild,
FG15(1-7)
IEEE DOI
1508
Internet
BibRef
Peng, X.[Xi],
Huang, J.Z.[Jun-Zhou],
Hu, Q.[Qiong],
Zhang, S.T.[Shao-Ting],
Metaxas, D.N.,
Three-dimensional head pose estimation in-the-wild,
FG15(1-6)
IEEE DOI
1508
image representation
BibRef
El-Barkouky, A.[Ahmed],
Shalaby, A.[Ahmed],
Mahmoud, A.[Ali],
Farag, A.A.[Aly A.],
Selective part models for detecting partially occluded faces in the
wild,
ICIP14(268-272)
IEEE DOI
1502
Barium; FDDB; Face Detection; Part models; Partial occlusion; SPM
BibRef
Bhat, K.K.S.,
Kannala, J.H.[Ju-Ho],
Heikkilä, J.[Janne],
3D Point Representation For Pose Estimation: Accelerated SIFT vs ORB,
SCIA15(79-91).
Springer DOI
1506
BibRef
Ylioinas, J.[Juha],
Kannala, J.H.[Ju-Ho],
Hadid, A.[Abdenour],
Pietikäinen, M.[Matti],
Unsupervised learning of overcomplete face descriptors,
Biometrics15(75-83)
IEEE DOI
1510
BibRef
And:
Face Recognition Using Smoothed High-Dimensional Representation,
SCIA15(516-529).
Springer DOI
1506
BibRef
Earlier: A1, A3, A2, A4:
An In-depth Examination of Local Binary Descriptors in Unconstrained
Face Recognition,
ICPR14(4471-4476)
IEEE DOI
1412
Benchmark testing
BibRef
Barr, J.R.[Jeremiah R.],
Bowyer, K.W.[Kevin W.],
Flynn, P.J.[Patrick J.],
The effectiveness of face detection algorithms in unconstrained crowd
scenes,
WACV14(1020-1027)
IEEE DOI
1406
Approximation algorithms
BibRef
Omri, F.[Faten],
Foufou, S.[Sebti],
Abidi, M.[Mongi],
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ICISP14(549-557).
Springer DOI
1406
BibRef
Qiu, J.Q.[Jie-Qiong],
Zhang, Y.[Ya],
Sun, J.[Jun],
Face recogntion in open world environment,
VCIP13(1-6)
IEEE DOI
1402
face recognition
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Herrmann, C.[Christian],
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Maximizing face recognition performance for video data under time
constraints by using a cascade,
AVSS14(181-186)
IEEE DOI
1411
Databases
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Herrmann, C.[Christian],
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Beyerer, J.[Jürgen],
Residual vs. Inception vs. Classical Networks for Low-Resolution Face
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SCIA17(II: 377-388).
Springer DOI
1706
BibRef
Earlier:
Low-Quality Video Face Recognition with Deep Networks and Polygonal
Chain Distance,
DICTA16(1-7)
IEEE DOI
1701
BibRef
And:
Low-resolution Convolutional Neural Networks for video face
recognition,
AVSS16(221-227)
IEEE DOI
1611
Face
BibRef
Herrmann, C.,
Extending a local matching face recognition approach to
low-resolution video,
AVSS13(460-465)
IEEE DOI
1311
face recognition
BibRef
Masi, I.[Iacopo],
Lisanti, G.[Giuseppe],
Bagdanov, A.D.[Andrew D.],
Pala, P.[Pietro],
del Bimbo, A.[Alberto],
Using 3D Models to Recognize 2D Faces in the Wild,
SISM13(775-780)
IEEE DOI
1309
3D Models;Face Recognition;PTZ Camera
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Tan, C.W.[Chun-Wei],
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Human identification from at-a-distance images by simultaneously
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ICPR12(553-556).
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Rudrani, S.[Shiva],
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ICIAR11(II: 212-221).
Springer DOI
1106
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Mostafa, E.A.[Eslam A.],
Ali, A.A.[Asem A.],
Alajlan, N.[Naif],
Farag, A.A.[Aly A.],
Pose Invariant Approach for Face Recognition at Distance,
ECCV12(VI: 15-28).
Springer DOI
1210
BibRef
El-Barkouky, A.[Ahmed],
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Womble, P.[Phil],
Face detection at a distance using saliency maps,
Biometrics12(31-36).
IEEE DOI
1207
BibRef
Rara, H.M.[Ham M.],
Ali, A.A.[Asem A.],
Elhabian, S.Y.[Shireen Y.],
Starr, T.L.[Thomas L.],
Farag, A.A.[Aly A.],
Face Recognition at-a-Distance Using Texture, Dense- and Sparse-Stereo
Reconstruction,
ICPR10(1221-1224).
IEEE DOI
1008
BibRef
Rara, H.M.[Ham M.],
Elhabian, S.Y.[Shireen Y.],
Ali, A.A.[Asem A.],
Gault, T.[Travis],
Miller, M.[Mike],
Starr, T.L.[Thomas L.],
Farag, A.A.[Aly A.],
A Framework for Long Distance Face Recognition Using Dense and
Sparse Stereo Reconstruction,
ISVC09(I: 774-783).
Springer DOI
0911
BibRef
Abdelrahman, M.[Mostafa],
Ali, A.M.[Asem M.],
Elhabian, S.Y.[Shireen Y.],
Rara, H.M.[Ham M.],
Farag, A.A.[Aly A.],
A passive stereo system for 3D human face reconstruction and
recognition at a distance,
Biometrics12(17-22).
IEEE DOI
1207
BibRef
Rara, H.M.[Ham M.],
Elhabian, S.Y.[Shireen Y.],
Ali, A.M.[Asem M.],
Miller, M.[Mike],
Starr, T.L.[Thomas L.],
Farag, A.A.[Aly A.],
Distant face recognition based on sparse-stereo reconstruction,
ICIP09(4141-4144).
IEEE DOI
0911
BibRef
And:
Face recognition at-a-distance based on sparse-stereo reconstruction,
Biometrics09(27-32).
IEEE DOI
0906
BibRef
Tome, P.[Pedro],
Fierrez-Aguilar, J.[Julian],
Fairhurst, M.C.,
Ortega-Garcia, J.[Javier],
Acquisition Scenario Analysis for Face Recognition at a Distance,
ISVC10(I: 461-468).
Springer DOI
1011
BibRef
Tome, P.[Pedro],
Fierrez-Aguilar, J.[Julian],
Alonso-Fernandez, F.[Fernando],
Ortega-Garcia, J.[Javier],
Scenario-based score fusion for face recognition at a distance,
Biometrics10(67-73).
IEEE DOI
1006
BibRef
Liu, R.[Rong],
Gao, X.F.[Xiu-Feng],
Chu, R.F.[Ru-Feng],
Zhu, X.X.[Xiang-Xin],
Li, S.Z.[Stan Z.],
Tracking and Recognition of Multiple Faces at Distances,
ICB07(513-522).
Springer DOI
0708
BibRef
Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Face Recognition Systems Using Neural Networks, Learning .