300 Videos in the Wild,
2015
Dataset, Faces.
WWW Link. Used for the ICCV 2015 workshop challenge.
WIDER Attribute dataset,
2016.
WWW Link.
Dataset, Faces.
See also Human Attribute Recognition by Deep Hierarchical Contexts.
Description of the Collection of Facial Images,
2007
Dataset, Faces.
HTML Version. Essex collection of faces. 395 people, 20 images each.
Annotated Facial Dataset,
2007
Dataset, Faces.
WWW Link.
The CMU Multi-PIE Face Database,
2010
Dataset, Faces.
WWW Link.
It contains 337 subjects, captured under 15 view points and 19
illumination conditions in four recording sessions for a total of more
than 750,000 images.
FaceScrub Annotated Face Dataset,
2014
Dataset, Faces.
HTML Version.
100,000 images of 530 people. Acquired from internet search with rejection
of pictures that do not match.
See also data-driven approach to cleaning large face datasets, A.
GVVPerfcapEva Repository of Evaluation Data Sets,
2015
Dataset, Faces.
Dataset, Human Motion.
Dataset, Hand Tracking.
WWW Link. A set of dataset including:
GVVPerfCapEva: IDT - Full body skeletal motion capture results from from body-worn inertial sensor data and depth camera recordings GVVPerfCapEva: Dexter 1: Evaluation data set for 3D hand tracking with depth and multi-view video data GVVPerfCapEva: PDT 2013: Body shape estimation and real-time motion capture with a depth camera GVVPerfcapEva: BinoCap - Dense 3D full-body performance capture with handheld stereo cameras (single + multiple person(s)) GVVPerfcapEva: MonFacecCap - Monocular dense face performance capture GVVPerfCapEva: MVIC - markerless multi-view performance capture of multiple interacting characters GVVPerfCapEva: HKIC: Performance capture of interacting characters with handheld Kinects
MPII Human Shape,
2015
Dataset, Human Pose.
WWW Link. Expressive 3D human body shape models and tools for human shape space building.
UB KinFace Database,
2011
Dataset, Faces.
HTML Version.
Yale Face Database,
Online2006.
First is 165 images.
HTML Version. And
5760 single light source images of 10 subjects each seen under
576 viewing conditions
HTML Version.
Dataset, Faces.
BibRef
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The University of Oulu Physics-Based Face Database,
2000.
125 different faces each in 16 different camera
calibration and illumination conditions.
WWW Link.
Dataset, Faces.
The University of Oulu Face Video Database,
2002.
WWW Link.
Dataset, Faces.
The CAS-PEAL Large-Scale Chinese Face Database
and Baseline Evaluations,
2004.
9,594 images of 1040 individuals (595 males and 445 females)
with varying Pose, Expression, Accessory, and Lighting
HTML Version.
Dataset, Faces.
MIT Face Recognition Database,
Online2000
Fi
Dataset, Faces.
HTML Version.
HTML Version. First one is small (19X19) images.
Second one has training and test data.
BibRef
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The UMIST Face Database,
1998.
Face Recognition.
HTML Version.
Dataset, Faces.
NIST Mugshot Identification Database,
2002.
HTML Version.
Dataset, Faces.
IARPA Janus Benchmark A (IJB-A) dataset,
2017.
WWW Link.
Dataset, Faces.
The ORL Database of Faces,
1992-1994.
More recently called the AT&T database.
HTML Version.
Dataset, Faces.
PubFig: Public Figures Face Database,
2015
Dataset, Faces.
WWW Link.
58,797 images of 200 people collected from the internet.
Refer to:
See also Attribute and simile classifiers for face verification.
Peer, P.[Peter],
CVL Face Database,
Online1999.
Dataset, Faces.
HTML Version. 114 people, 7 images each.
BibRef
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2001
Dataset, Faces.
Dataset, Expressions.
Dataset, Gesture.
HTML Version. A variety of datasets for face recognition, expression recognition,
gesture recognition, and video surveillance.
See also POSTECH face database (PF07) and performance evaluation, The.
Face Recognition Vendor Test 2006,
Online2006.
WWW Link.
Dataset, Faces.
WWW Link.
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Dataset, Faces. 181 poses 1 degree apart plus lighting (direction) changes.
See also Arizona State University.
0906
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2015
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WWW Link. A database of face videos designed for studying the problem of
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Oxford Town Center,
2009
Dataset, Human Tracking.
WWW Link.
Pedestrian detection and tracking.
CHUK Datasets,
2009
Dataset, Pedestrian Tracking.
Dataset, Crowd Analysis.
Dataset, Pedestrian Detection.
Dataset, Re-Identification.
HTML Version.
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A View From Somewhere (AVFS),
2023
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Learned-Miller, E.G.[Erick G.],
FDDB: Face Detection Data Set and Benchmark,
UMass2010, Technical Report 2010-009.
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Dataset, Faces. annotations for 5171 faces in a set of 2845 images.
Subset of
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Mahoor, M.H.[Mohammad H.],
Extended DISFA Dataset: Investigating Posed and Spontaneous Facial
Expressions,
Affect16(1452-1459)
IEEE DOI
1612
BibRef
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Chu, T.Y.[Tsu-Ying],
A Framework for Making Face Detection Benchmark Databases,
CirSysVideo(24), No. 2, February 2014, pp. 230-241.
IEEE DOI
1403
benchmark testing
BibRef
Zhang, X.[Xing],
Yin, L.J.[Li-Jun],
Cohn, J.F.[Jeffrey F.],
Canavan, S.[Shaun],
Reale, M.[Michael],
Horowitz, A.[Andy],
Liu, P.[Peng],
Girard, J.M.[Jeffrey M.],
BP4D-Spontaneous: a high-resolution spontaneous 3D dynamic facial
expression database,
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Elsevier DOI
1410
BibRef
Earlier: A1, A2, A3, A4, A5, A6, A7, Only:
A high-resolution spontaneous 3D dynamic facial expression database,
FG13(1-6)
IEEE DOI
1309
Dataset, Facial Expressions. emotion recognition
3D facial expression
BibRef
Yin, L.J.[Li-Jun],
Chen, X.C.[Xiao-Chen],
Sun, Y.[Yi],
Worm, T.[Tony],
Reale, M.[Michael],
A high-resolution 3D dynamic facial expression database,
FG08(1-6).
IEEE DOI
0809
Dataset, Facial Expressions.
BibRef
Xu, Y.[Yong],
Fang, X.Z.[Xiao-Zhao],
Li, X.L.[Xue-Long],
Yang, J.[Jiang],
You, J.,
Liu, H.[Hong],
Teng, S.H.[Shao-Hua],
Data Uncertainty in Face Recognition,
Cyber(44), No. 10, October 2014, pp. 1950-1961.
IEEE DOI
1410
face recognition
BibRef
Abaza, A.[Ayman],
Harrison, M.A.[Mary Ann],
Bourlai, T.[Thirimachos],
Ross, A.,
Design and evaluation of photometric image quality measures for
effective face recognition,
IET-Bio(3), No. 4, 2014, pp. 314-324.
DOI Link
1504
BibRef
Earlier: A1, A2, A3:
Quality metrics for practical face recognition,
ICPR12(3103-3107).
WWW Link.
1302
design engineering
BibRef
Mandasari, M.I.,
Gunther, M.,
Wallace, R.,
Saeidi, R.,
Marcel, S.,
van Leeuwen, D.A.,
Score calibration in face recognition,
IET-Bio(3), No. 4, 2014, pp. 246-256.
DOI Link
1504
biometrics (access control)
BibRef
Hassaballah, M.,
Aly, S.,
Face recognition: challenges, achievements and future directions,
IET-CV(9), No. 4, 2015, pp. 614-626.
DOI Link
1509
face recognition
BibRef
Tsifouti, A.,
Triantaphillidou, S.,
Larabi, M.C.,
Bilissi, E.,
Psarrou, A.,
A case study in identifying acceptable bitrates for human face
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SP:IC(36), No. 1, 2015, pp. 14-28.
Elsevier DOI
1509
CCTV recording systems
BibRef
Mahmood, Z.,
Ali, T.,
Khan, S.U.,
Effects of pose and image resolution on automatic face recognition,
IET-Bio(5), No. 2, 2016, pp. 111-119.
DOI Link
1606
biometrics (access control)
BibRef
Strickland, E.,
Face recognition tech goes on trial,
Spectrum(54), No. 1, January 2017, pp. 40-41.
IEEE DOI
1702
[Top Tech 2017]
face recognition
BibRef
Yu, J.[Jun],
Sun, K.[Kejia],
Gao, F.[Fei],
Zhu, S.[Suguo],
Face biometric quality assessment via light CNN,
PRL(107), 2018, pp. 25-32.
Elsevier DOI
1805
Biometric quality assessment,
Convolutional neural networks (CNNs), Face recognition,
Video surveillance
BibRef
Arandjelovic, O.D.[Ognjen D.],
Reimagining the central challenge of face recognition:
Turning a problem into an advantage,
PR(83), 2018, pp. 388-400.
Elsevier DOI
1808
Meta-algorithm, Paradigm change, Retrieval, Intra-class,
Inter-class, Similarity, Dissimilarity
BibRef
Zheng, Z.C.[Zhi-Chao],
Sun, H.J.[Huai-Jiang],
Jointly discriminative projection and dictionary learning for domain
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PR(90), 2019, pp. 325-336.
Elsevier DOI
1903
Collaborative representation, Dimensionality reduction,
Dictionary learning, Domain adptation
BibRef
Zhang, Q.[Quan],
Sun, H.J.[Huai-Jiang],
Probabilistic collaborative representation based orthogonal
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JVCIR(55), 2018, pp. 106-114.
Elsevier DOI
1809
Image set, Face recognition,
Probabilistic collaborative representation,
Orthogonal discriminative projection
BibRef
Dey, A.[Aniruddha],
Chowdhury, S.[Shiladitya],
Sing, J.K.[Jamuna Kanta],
Performance evaluation on image fusion techniques for face recognition,
IJCVR(8), No. 5, 2018, pp. 455-475.
DOI Link
1810
BibRef
Kugler, L.[Logan],
Being Recognized Everywhere,
CACM(62), No. 2, February 2019, pp. 17-19.
DOI Link
1902
News, analysis of facial recognition uses.
BibRef
Soundararajan, R.[Rajiv],
Biswas, S.[Soma],
Machine vision quality assessment for robust face detection,
SP:IC(72), 2019, pp. 92-104.
Elsevier DOI
1902
BibRef
Bhattacharya, S.[Shubhobrata],
Rooj, S.[Suparna],
Routray, A.[Aurobinda],
QDF: A face database with varying quality,
SP:IC(74), 2019, pp. 13-20.
Elsevier DOI
1904
Face Quality Assessment, Face recognition, Super-resolution,
Fiducial point estimation, Face image database
BibRef
Bicego, M.[Manuele],
Grosso, E.[Enrico],
On the importance of local and global analysis in the judgment of
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IVC(92), 2019, pp. 103813.
Elsevier DOI
1912
Face analysis, Biometrics, Image matching,
Similarity-dissimilarity of visual content
BibRef
Al Jazaery, M.[Mohamad],
Guo, G.D.[Guo-Dong],
Automated cleaning of identity label noise in a large face dataset with
quality control,
IET-Bio(9), No. 1, January 2020, pp. 25-30.
DOI Link
2001
BibRef
Panetta, K.[Karen],
Wan, Q.W.[Qian-Wen],
Agaian, S.[Sos],
Rajeev, S.[Srijith],
Kamath, S.[Shreyas],
Rajendran, R.[Rahul],
Rao, S.P.[Shishir Paramathma],
Kaszowska, A.[Aleksandra],
Taylor, H.A.[Holly A.],
Samani, A.[Arash],
Yuan, X.[Xin],
A Comprehensive Database for Benchmarking Imaging Systems,
PAMI(42), No. 3, March 2020, pp. 509-520.
IEEE DOI
2002
Face, Face recognition, Databases,
Cameras, Image recognition, The tufts face database, cross-modality
BibRef
Dong, X.[Xingbo],
Kim, S.[Soohyung],
Jin, Z.[Zhe],
Hwang, J.Y.[Jung Yeon],
Cho, S.[Sangrae],
Teoh, A.B.J.[Andrew Beng Jin],
Open-set face identification with index-of-max hashing by learning,
PR(103), 2020, pp. 107277.
Elsevier DOI
2005
Secure open-set face identification, Index-of-max hashing,
Fusion, Privacy
BibRef
Ma, Y.H.[Yu-Hao],
Kan, M.[Meina],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Learning deep face representation with long-tail data:
An aggregate-and-disperse approach,
PRL(133), 2020, pp. 48-54.
Elsevier DOI
2005
Face recognition, Deep representation learning,
Long-tail distribution, Aggregate-and-disperse
BibRef
Wu, H.Z.[Hao-Zhan],
Han, H.[Hu],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Multi-View Consistent 3D GAN Inversion via Bidirectional Encoder,
FG24(1-10)
IEEE DOI Code:
WWW Link.
2408
Codes, Face recognition, Interference, Gesture recognition, Cameras,
Image reconstruction
BibRef
Han, C.R.[Chun-Rui],
Shan, S.G.[Shi-Guang],
Kan, M.[Meina],
Wu, S.Z.[Shu-Zhe],
Chen, X.L.[Xi-Lin],
Personalized Convolution for Face Recognition,
IJCV(130), No. 2, February 2022, pp. 344-362.
Springer DOI
2202
BibRef
Liu, X.[Xin],
Kan, M.[Meina],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Noisy Face Image Sets Refining Collaborated with Discriminant Feature
Space Learning,
FG17(544-550)
IEEE DOI
1707
Face, Face recognition, Nickel, Noise measurement, Robustness,
Search engines, Visualization
BibRef
Lathuiličre, S.[Stéphane],
Mesejo, P.[Pablo],
Alameda-Pineda, X.[Xavier],
Horaud, R.[Radu],
A Comprehensive Analysis of Deep Regression,
PAMI(42), No. 9, September 2020, pp. 2065-2081.
IEEE DOI
2008
BibRef
And:
DeepGUM: Learning Deep Robust Regression with a Gaussian-Uniform
Mixture Model,
ECCV18(VI: 205-221).
Springer DOI
1810
Computer architecture, Task analysis, Pose estimation,
Systematics, Deep learning, Benchmark testing,
facial landmark detection
BibRef
Cheema, U.[Usman],
Moon, S.[Seungbin],
Sejong face database: A multi-modal disguise face database,
CVIU(208-209), 2021, pp. 103218.
Elsevier DOI
2106
Dataset, Face Recognition. Biometrics, Disguise recognition, Face database,
Face recognition, Multi-modal
BibRef
Bhattacharya, S.[Shubhobrata],
Kyal, C.[Chirag],
Routray, A.[Aurobinda],
Simplified Face Quality Assessment (SFQA),
PRL(147), 2021, pp. 108-114.
Elsevier DOI
2106
Face quality assessment, Hashing, Convolution neural network, Face recognition
BibRef
Lago, F.[Federica],
Pasquini, C.[Cecilia],
Böhme, R.[Rainer],
Dumont, H.[Hélčne],
Goffaux, V.[Valérie],
Boato, G.[Giulia],
More Real Than Real:
A Study on Human Visual Perception of Synthetic Faces,
SPMag(39), No. 1, January 2022, pp. 109-116.
IEEE DOI
2201
[Applications Corner]
Social networking (online), User-generated content,
Medical services, Streaming media, Media, Real-time systems, Facial recognition
BibRef
Marwa, K.[Kebir],
Kais, O.[Ouni],
Perspectives Of Classical Methods Of Face Recognition,
ISCV22(1-8)
IEEE DOI
2208
Training, Support vector machines, Dimensionality reduction,
Deep learning, Image recognition, Databases, Face recognition,
SVM
BibRef
Sami, S.M.[Shoaib Meraj],
McCauley, J.[John],
Soleymani, S.[Sobhan],
Nasrabadi, N.M.[Nasser M.],
Dawson, J.[Jeremy],
Benchmarking human face similarity using identical twins,
IET-Bio(11), No. 5, 2022, pp. 459-484.
DOI Link
2210
facial similarity, facial recognition, identical twins, look-alikes
BibRef
Medvedev, I.[Iurii],
Tremoço, J.[Joăo],
Mano, B.[Beatriz],
Santo, L.E.[Luís Espírito],
Gonçalves, N.[Nuno],
Towards understanding the character of quality sampling in deep
learning face recognition,
IET-Bio(11), No. 5, 2022, pp. 498-511.
DOI Link
2210
Inconsistency between training collection and real-world images.
BibRef
Zhu, Z.[Zheng],
Huang, G.[Guan],
Deng, J.K.[Jian-Kang],
Ye, Y.[Yun],
Huang, J.J.[Jun-Jie],
Chen, X.Z.[Xin-Ze],
Zhu, J.[Jiagang],
Yang, T.[Tian],
Du, D.L.[Da-Long],
Lu, J.W.[Ji-Wen],
Zhou, J.[Jie],
WebFace260M: A Benchmark for Million-Scale Deep Face Recognition,
PAMI(45), No. 2, February 2023, pp. 2627-2644.
IEEE DOI
2301
BibRef
Earlier: A1, A2, A3, A4, A5, A6, A7, A8, A10, A9, A11:
WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep
Face Recognition,
CVPR21(10487-10497)
IEEE DOI
2111
Face recognition, Benchmark testing, Training, Protocols, Training data,
Standards, Internet, Large-scale face recognition, biometric authentication.
Training, Knowledge engineering, Protocols, Face recognition,
Pipelines, Training data, Benchmark testing
BibRef
Fan, S.J.[Shao-Jing],
Shen, Z.[Zhiqi],
Koenig, B.L.[Bryan L.],
Ng, T.T.[Tian-Tsong],
Kankanhalli, M.S.[Mohan S.],
When and Why Static Images Are More Effective Than Videos,
AffCom(14), No. 1, January 2023, pp. 308-320.
IEEE DOI
2303
Videos, Optical imaging, Observers, Entropy, Visualization,
Face recognition, Emotion recognition, Emotions, deep neural network
BibRef
Boutros, F.[Fadi],
Struc, V.[Vitomir],
Fierrez, J.[Julian],
Damer, N.[Naser],
Synthetic data for face recognition: Current state and future prospects,
IVC(135), 2023, pp. 104688.
Elsevier DOI
2306
Face recognition, Synthetic data, Biometrics
BibRef
Guo, Y.L.[Yu-Lan],
Wang, H.[Hanyun],
Wang, L.G.[Long-Guang],
Lei, Y.J.[Yig-Jie],
Liu, L.[Li],
Bennamoun, M.[Mohammed],
3D Face Recognition: Two Decades of Progress and Prospects,
Surveys(56), No. 3, October 2023, pp. xx-yy.
DOI Link
2311
Survey, Facial Expressions. pose variation, deep learning, local feature, facial occlusion,
facial expression, 3D face recognition
BibRef
Vareto, R.H.[Rafael Henrique],
Linghu, Y.[Yu],
Boult, T.E.[Terrance Edward],
Schwartz, W.R.[William Robson],
Günther, M.[Manuel],
Open-set face recognition with maximal entropy and Objectosphere loss,
IVC(141), 2024, pp. 104862.
Elsevier DOI
2402
Neural networks, Biometrics, Classification, Face recognition,
Open-set, Watchlist
BibRef
Joshi, I.[Indu],
Grimmer, M.[Marcel],
Rathgeb, C.[Christian],
Busch, C.[Christoph],
Bremond, F.[Francois],
Dantcheva, A.[Antitza],
Synthetic Data in Human Analysis: A Survey,
PAMI(46), No. 7, July 2024, pp. 4957-4976.
IEEE DOI
2406
Synthetic data, Training, Data models, Mathematical models, Surveys,
Adaptation models, Biological system modeling
BibRef
Guerdelli, H.[Hajer],
Ferrari, C.[Claudio],
Berretti, S.[Stefano],
del Bimbo, A.[Alberto],
IMEmo: An Interpersonal Relation Multi-Emotion Dataset,
FG24(1-10)
IEEE DOI
2408
Emotion recognition, Protocols, Annotations, Mood, Face recognition,
Benchmark testing, Motion pictures
BibRef
Neto, P.C.[Pedro C.],
Mamede, R.M.[Rafael M.],
Albuquerque, C.[Carolina],
Gonçalves, T.[Tiago],
Sequeira, A.F.[Ana F.],
Massively Annotated Datasets for Assessment of Synthetic and Real
Data in Face Recognition,
FG24(1-7)
IEEE DOI
2408
Deep learning, Privacy, Annotations, Generative AI, Face recognition,
Computational modeling, Gesture recognition
BibRef
Medvedev, I.[Iurii],
Shadmand, F.[Farhad],
Gonçalves, N.[Nuno],
Young Labeled Faces in the Wild (YLFW):
A Dataset for Children Faces Recognition,
FG24(1-10)
IEEE DOI
2408
Training, Image quality, Deep learning, Protocols, Face recognition,
Image edge detection, Gesture recognition
BibRef
Atzori, A.[Andrea],
Boutros, F.[Fadi],
Damer, N.[Naser],
Fenu, G.[Gianni],
Marras, M.[Mirko],
If It's Not Enough, Make It So: Reducing Authentic Data Demand in
Face Recognition through Synthetic Faces,
FG24(1-10)
IEEE DOI
2408
Training, Data privacy, Accuracy, Face recognition,
Gesture recognition, Data collection, Data augmentation
BibRef
Kuzdeuov, A.[Askat],
Taratynova, D.[Darya],
Tleuliyev, A.[Alim],
Varol, H.A.[Huseyin Atakan],
OpenThermalPose: An Open-Source Annotated Thermal Human Pose Dataset
and Initial YOLOv8-Pose Baselines,
FG24(1-8)
IEEE DOI Code:
WWW Link.
2408
Privacy, Annotations, Source coding, Pose estimation, Lighting,
Medical services, Motion capture
BibRef
Shahreza, H.O.[Hatef Otroshi],
Ecabert, C.[Christophe],
George, A.[Anjith],
Unnervik, A.[Alexander],
Marcel, S.[Sébastien],
di Domenico, N.[Nicolň],
Borghi, G.[Guido],
Maltoni, D.[Davide],
Boutros, F.[Fadi],
Vogel, J.[Julia],
Damer, N.[Naser],
Sánchez-Pérez, Á.[Ángela],
Mas-Candela, E.[Enrique],
Calvo-Zaragoza, J.[Jorge],
Biesseck, B.[Bernardo],
Vidal, P.[Pedro],
Granada, R.[Roger],
Menotti, D.[David],
De Andres-Tame, I.[Ivan],
La Cava, S.M.[Simone Maurizio],
Concas, S.[Sara],
Melzi, P.[Pietro],
Tolosana, R.[Ruben],
Vera-Rodriguez, R.[Ruben],
Perelli, G.[Gianpaolo],
Orrů, G.[Giulia],
Marcialis, G.L.[Gian Luca],
Fierrez, J.[Julian],
SDFR: Synthetic Data for Face Recognition Competition,
FG24(1-9)
IEEE DOI
2408
Training, Ethics, Data privacy, Law, Face recognition,
Gesture recognition, Data models
BibRef
di Domenico, N.[Nicolň],
Borghi, G.[Guido],
Franco, A.[Annalisa],
Maltoni, D.[Davide],
ONOT: a High-Quality ICAO-compliant Synthetic Mugshot Dataset,
FG24(1-10)
IEEE DOI Code:
WWW Link.
2408
ISO Standards, Standards organizations, Organizations,
Gesture recognition, Reproducibility of results, IEC Standards
BibRef
Lu, Y.H.[Yu-Hang],
Xu, Z.W.[Ze-Wei],
Ebrahimi, T.[Touradj],
Explainable Face Verification via Feature-Guided Gradient
Backpropagation,
FG24(1-5)
IEEE DOI
2408
Backpropagation, Visualization, Face recognition, Machine vision,
Current measurement, Gesture recognition, Reliability
BibRef
Rathgeb, C.,
Ibsen, M.,
Hartmann, D.,
Hradetzky, S.,
Ólafsdóttir, B.,
Testing the Performance of Face Recognition for People with Down
Syndrome,
FG24(1-5)
IEEE DOI
2408
Image quality, Training, Video on demand, Image recognition,
Image databases, Face recognition, Gesture recognition
BibRef
Baltsou, G.[Georgia],
Sarridis, I.[Ioannis],
Koutlis, C.[Christos],
Papadopoulos, S.[Symeon],
SDFD: Building a Versatile Synthetic Face Image Dataset with Diverse
Attributes,
FG24(1-10)
IEEE DOI
2408
Training, Systematics, Face recognition, Text to image,
Gesture recognition, Skin, Robustness
BibRef
Huber, M.[Marco],
Luu, A.T.[Anh Thi],
Damer, N.[Naser],
Recognition Performance Variation Across Demographic Groups Through
the Eyes of Explainable Face Recognition,
FG24(1-10)
IEEE DOI
2408
Visualization, Face recognition, Focusing, Gesture recognition,
Data models, Task analysis, Facial features
BibRef
Saritas, E.[Erdi],
Ekenel, H.K.[Hazam Kemal],
Analyzing the Effect of Combined Degradations on Face Recognition,
FG24(1-5)
IEEE DOI Code:
WWW Link.
2408
Degradation, Analytical models, Codes, Accuracy, Face recognition,
Pipelines, Gesture recognition
BibRef
Song, S.Y.[Si-Yang],
Spitale, M.[Micol],
Luo, C.[Cheng],
Palmero, C.[Cristina],
Barquero, G.[German],
Zhu, H.[Hengde],
Escalera, S.[Sergio],
Valstar, M.[Michel],
Baur, T.[Tobias],
Ringeval, F.[Fabien],
André, E.[Elisabeth],
Gunes, H.[Hatice],
REACT 2024: the Second Multiple Appropriate Facial Reaction
Generation Challenge,
FG24(1-5)
IEEE DOI Code:
WWW Link.
2408
Image segmentation, Codes, Face recognition, Machine learning,
Gesture recognition, Benchmark testing, Image sequences
BibRef
Dubiel, A.[Agnieszka],
Kaminska, D.[Dorota],
Zwolinski, G.[Grzegorz],
Jafari, A.A.[Akbar Anbar],
Vinodkumar, P.K.[Prasoon Kumar],
Avots, E.[Eglis],
Jacques, J.C.S.[Julio C. S.],
Escalera, S.[Sergio],
Anbajafari, G.[Gholamreza],
Brain Responses to Emotional Avatars Challenge: Dataset and Results,
FG24(1-8)
IEEE DOI
2408
Emotion recognition, Accuracy, Machine learning algorithms,
Avatars, Refining, Virtual environments, Machine learning
BibRef
Lu, Y.H.[Yu-Hang],
Xu, Z.W.[Ze-Wei],
Ebrahimi, T.[Touradj],
Towards Visual Saliency Explanations of Face Verification,
WACV24(4714-4723)
IEEE DOI
2404
Visualization, Face recognition, Decision making,
Convolutional neural networks, Task analysis, Algorithms
BibRef
Huber, M.[Marco],
Luu, A.T.[Anh Thi],
Terhörst, P.[Philipp],
Damer, N.[Naser],
Efficient Explainable Face Verification based on Similarity Score
Argument Backpropagation,
WACV24(4724-4733)
IEEE DOI Code:
WWW Link.
2404
Backpropagation, Visualization, Protocols, Frequency modulation,
Face recognition, Computational modeling, Algorithms, Explainable
BibRef
DeAndres-Tame, I.[Ivan],
Tolosana, R.[Ruben],
Melzi, P.[Pietro],
Vera-Rodriguez, R.[Ruben],
Kim, M.[Minchul],
Rathgeb, C.[Christian],
Liu, X.M.[Xiao-Ming],
Morales, A.[Aythami],
Fierrez, J.[Julian],
Ortega-Garcia, J.[Javier],
Zhong, Z.Z.[Zhi-Zhou],
Huang, Y.[Yuge],
Mi, Y.X.[Yu-Xi],
Ding, S.H.[Shou-Hong],
Zhou, S.[Shuigeng],
He, S.[Shuai],
Fu, L.Z.[Ling-Zhi],
Cong, H.[Heng],
Zhang, R.[Rongyu],
Xiao, Z.H.[Zhi-Hong],
Smirnov, E.[Evgeny],
Pimenov, A.[Anton],
Grigorev, A.[Aleksei],
Timoshenko, D.[Denis],
Asfaw, K.M.[Kaleb Mesfin],
Low, C.Y.[Cheng Yaw],
Liu, H.[Hao],
Wang, C.[Chuyi],
Zuo, Q.[Qing],
He, Z.X.[Zhi-Xiang],
Shahreza, H.O.[Hatef Otroshi],
George, A.[Anjith],
Unnervik, A.[Alexander],
Rahimi, P.[Parsa],
Marcel, S.[Sébastien],
Neto, P.C.[Pedro C.],
Huber, M.[Marco],
Kolf, J.N.[Jan Niklas],
Damer, N.[Naser],
Boutros, F.[Fadi],
Cardoso, J.S.[Jaime S.],
Sequeira, A.F.[Ana F.],
Atzori, A.[Andrea],
Fenu, G.[Gianni],
Marras, M.[Mirko],
truc, V.[Vitomir],
Yu, J.[Jiang],
Li, Z.J.[Zhang-Jie],
Li, J.[Jichun],
Zhao, W.S.[Wei-Song],
Lei, Z.[Zhen],
Zhu, X.Y.[Xiang-Yu],
Zhang, X.Y.[Xiao-Yu],
Biesseck, B.[Bernardo],
Vidal, P.[Pedro],
Coelho, L.[Luiz],
Granada, R.[Roger],
Menotti, D.[David],
Second Edition FRCSyn Challenge at CVPR 2024: Face Recognition
Challenge in the Era of Synthetic Data,
CVPRWS24(3173-3183)
IEEE DOI
2410
Training, Data privacy, Protocols, Face recognition, Transforms,
Manuals, Machine learning, FRCSyn, Face Recognition, Synthetic Data,
Privacy
BibRef
Melzi, P.[Pietro],
Tolosana, R.[Ruben],
Vera-Rodriguez, R.[Ruben],
Kim, M.[Minchul],
Rathgeb, C.[Christian],
Liu, X.M.[Xiao-Ming],
DeAndres-Tame, I.[Ivan],
Morales, A.[Aythami],
Fierrez, J.[Julian],
Ortega-Garcia, J.[Javier],
Zhao, W.S.[Wei-Song],
Zhu, X.Y.[Xiang-Yu],
Yan, Z.[Zheyu],
Zhang, X.Y.[Xiao-Yu],
Wu, J.L.[Jin-Lin],
Lei, Z.[Zhen],
Tripathi, S.[Suvidha],
Kothari, M.[Mahak],
Zama, M.H.[Md Haider],
Deb, D.[Debayan],
Biesseck, B.[Bernardo],
Vidal, P.[Pedro],
Granada, R.[Roger],
Fickel, G.[Guilherme],
Führ, G.[Gustavo],
Menotti, D.[David],
Unnervik, A.[Alexander],
George, A.[Anjith],
Ecabert, C.[Christophe],
Shahreza, H.O.[Hatef Otroshi],
Rahimi, P.[Parsa],
Marcel, S.[Sébastien],
Sarridis, I.[Ioannis],
Koutlis, C.[Christos],
Baltsou, G.[Georgia],
Papadopoulos, S.[Symeon],
Diou, C.[Christos],
di Domenico, N.[Nicolň],
Borghi, G.[Guido],
Pellegrini, L.[Lorenzo],
Mas-Candela, E.[Enrique],
Sánchez-Pérez, Á.[Ángela],
Atzori, A.[Andrea],
Fenu, G.[Gianni],
Boutros, F.[Fadi],
Marras, M.[Mirko],
Damer, N.[Naser],
FRCSyn Challenge at WACV 2024: Face Recognition Challenge in the Era
of Synthetic Data,
LLVMCrive24(892-901)
IEEE DOI
2404
Measurement, Data privacy, Face recognition, Benchmark testing, Task analysis
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Chen, Y.Q.[Yuan-Qiong],
Wang, P.P.[Ping-Ping],
Ling, J.[Jing],
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Research on Face recognition based on Grey Wolf algorithm
optimization,
CVIDL23(329-333)
IEEE DOI
2403
Deep learning, Adaptation models, Image recognition,
Face recognition, Training data, Prediction algorithms,
Grey Wolf algorithm optimitization
BibRef
Patil, S.D.[Snehal D.],
Bartakke, P.P.[Prashant P.],
Sutaone, M.S.[Mukul S.],
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Techniques,
ICCVMI23(1-6)
IEEE DOI
2403
Art, Annotations, Face recognition, Streaming media, Cameras,
Inference algorithms, Safety, Face detection, mean average precision
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Melzi, P.[Pietro],
Rathgeb, C.[Christian],
Tolosana, R.[Ruben],
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Lawatsch, D.[Dominik],
Domin, F.[Florian],
Schaubert, M.[Maxim],
GANDiffFace: Controllable Generation of Synthetic Datasets for Face
Recognition with Realistic Variations,
AMFG23(3078-3087)
IEEE DOI
2401
BibRef
Hast, A.[Anders],
Consensus Ranking for Efficient Face Image Retrieval:
A Novel Method for Maximising Precision and Recall,
CIAP23(I:159-170).
Springer DOI
2312
BibRef
Bai, X.Y.[Xia-Ying],
Zheng, W.X.[Wen-Xian],
Yang, W.M.[Wen-Ming],
Wang, G.J.[Gui-Jin],
Liao, Q.M.[Qing-Min],
Hard Samples Based Margin Loss for Face Verification,
ICIP23(3513-3517)
IEEE DOI
2312
BibRef
Wu, H.[Haiyu],
Bezold, G.[Grace],
Günther, M.[Manuel],
Boult, T.[Terrance],
King, M.C.[Michael C.],
Bowyer, K.W.[Kevin W.],
Consistency and Accuracy of CelebA Attribute Values,
VDU23(3258-3266)
IEEE DOI
2309
WWW Link. Evaluation of facial attributes.
BibRef
Pérez, J.C.[Juan C.],
Alfarra, M.[Motasem],
Thabet, A.[Ali],
Arbeláez, P.[Pablo],
Ghanem, B.[Bernard],
Towards Characterizing the Semantic Robustness of Face Recognition,
LXCV23(315-325)
IEEE DOI
2309
BibRef
Chen, M.Q.[Ming-Qiang],
Liu, L.[Lizhe],
Chen, X.[Xiaohao],
Zhu, S.[Siyu],
GB-Cosface: Rethinking Softmax-based Face Recognition from the
Perspective of Open Set Classification,
ACCV22(IV:35-51).
Springer DOI
2307
BibRef
Sankaran, N.[Nishant],
Mohan, D.D.[Deen Dayal],
Tulyakov, S.[Sergey],
Setlur, S.[Srirangaraj],
Govindaraju, V.[Venugopal],
TADPool: Target Adaptive Pooling for Set Based Face Recognition,
FG21(1-8)
IEEE DOI
2303
Q-factor, Adaptive systems, Face recognition, Focusing,
Gesture recognition, Mirrors
BibRef
Knoche, M.[Martin],
Hormann, S.[Stefan],
Rigoll, G.[Gerhard],
Cross-Quality LFW: A Database for Analyzing Cross- Resolution Image
Face Recognition in Unconstrained Environments,
FG21(1-5)
IEEE DOI
2303
Image quality, Protocols, Image resolution, Databases,
Face recognition, Benchmark testing, Predictive models
BibRef
Shen, B.[Bingyu],
RichardWebster, B.[Brandon],
O'Toole, A.[Alice],
Bowyer, K.W.[Kevin W.],
Scheirer, W.J.[Walter J.],
A Study of the Human Perception of Synthetic Faces,
FG21(1-8)
IEEE DOI
2303
Face recognition, Psychology, Gesture recognition, Observers
BibRef
Franc, V.[Vojtech],
Yermakov, A.[Andrii],
Dominant subject recognition by Bayesian learning,
FG21(01-05)
IEEE DOI
2303
Faces which appear most frequently in a collection.
Image recognition, Protocols, Image databases, Face recognition,
Prediction algorithms
BibRef
Qu, T.Y.[Ting-Yu],
Tuytelaars, T.[Tinne],
Moens, M.F.[Marie-Francine],
Weakly Supervised Face Naming with Symmetry-Enhanced Contrastive Loss,
WACV23(3494-3503)
IEEE DOI
2302
Training, Adaptation models, Uncertainty, Computational modeling,
Neural networks, Cognition
BibRef
Boutros, F.[Fadi],
Grebe, J.H.[Jonas Henry],
Kuijper, A.[Arjan],
Damer, N.[Naser],
IDiff-Face: Synthetic-based Face Recognition through Fizzy
Identity-Conditioned Diffusion Models,
ICCV23(19593-19604)
IEEE DOI
2401
BibRef
Terhörst, P.[Philipp],
Ihlefeld, M.[Malte],
Huber, M.[Marco],
Damer, N.[Naser],
Kirchbuchner, F.[Florian],
Raja, K.[Kiran],
Kuijper, A.[Arjan],
QMagFace: Simple and Accurate Quality-Aware Face Recognition,
WACV23(3473-3483)
IEEE DOI
2302
Training, Image quality, Image recognition, Databases,
Face recognition, Computational modeling, Algorithms: Biometrics
BibRef
Bae, G.[Gwangbin],
de la Gorce, M.[Martin],
Baltruaitis, T.[Tadas],
Hewitt, C.[Charlie],
Chen, D.[Dong],
Valentin, J.[Julien],
Cipolla, R.[Roberto],
Shen, J.J.[Jing-Jing],
DigiFace-1M: 1 Million Digital Face Images for Face Recognition,
WACV23(3515-3524)
IEEE DOI
2302
Ethics, Error analysis, Face recognition, Computational modeling,
Pipelines, Lighting, Algorithms: Biometrics, face, gesture, body pose,
visual reasoning
BibRef
Zhang, M.Y.[Man-Yuan],
Song, G.L.[Guang-Lu],
Liu, Y.[Yu],
Li, H.S.[Hong-Sheng],
Towards Robust Face Recognition with Comprehensive Search,
ECCV22(XII:720-736).
Springer DOI
2211
BibRef
Wu, C.Y.[Cho-Ying],
Hsu, C.C.[Chin-Cheng],
Neumann, U.[Ulrich],
Cross-Modal Perceptionist: Can Face Geometry be Gleaned from Voices?,
CVPR22(10442-10451)
IEEE DOI
2210
Geometry, Visualization, Correlation, Numerical analysis,
Face recognition, Vision + X, Biometrics, Explainable computer vision
BibRef
Kim, M.C.[Min-Chul],
Jain, A.K.[Anil K.],
Liu, X.M.[Xiao-Ming],
AdaFace: Quality Adaptive Margin for Face Recognition,
CVPR22(18729-18738)
IEEE DOI
2210
Image quality, Training, Adaptation models, Codes, Face recognition,
Training data, Face and gestures, Recognition: detection,
retrieval
BibRef
Voo, K.T.R.[Kenny T. R.],
Jiang, L.M.[Li-Ming],
Loy, C.C.[Chen Change],
Delving into High-Quality Synthetic Face Occlusion Segmentation
Datasets,
VDU22(4710-4719)
IEEE DOI
2210
Codes, Annotations, Face recognition, Benchmark testing, Robustness
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Robbins, W.[Wes],
Boult, T.E.[Terrance E.],
On the Effect of Atmospheric Turbulence in the Feature Space of Deep
Face Recognition,
Biometrics22(1617-1625)
IEEE DOI
2210
Image quality, Extraterrestrial phenomena, Face recognition,
Atmospheric modeling, Computational modeling
BibRef
Kornilova, A.[Anastasiia],
Faizullin, M.[Marsel],
Pakulev, K.[Konstantin],
Sadkov, A.[Andrey],
Kukushkin, D.[Denis],
Akhmetyanov, A.[Azat],
Akhtyamov, T.[Timur],
Taherinejad, H.[Hekmat],
Ferrer, G.[Gonzalo],
SmartPortraits: Depth Powered Handheld Smartphone Dataset of Human
Portraits for State Estimation, Reconstruction and Synthesis,
CVPR22(21286-21297)
IEEE DOI
2210
Video sequences, Cameras, Sensor systems and applications,
Software, Trajectory, Synchronization, Datasets and evaluation,
RGBD sensors and analytics
BibRef
Luo, J.H.[Jia-Hao],
Khan, F.[Fahim],
Mori, I.[Issei],
de Silva, A.[Akila],
Ruezga, E.[Eric],
Davis, J.[James],
Face Models: How Good Does My Data Need To Be?,
ICIP21(3188-3192)
IEEE DOI
2201
Solid modeling, Reconstruction algorithms, Laser modes,
Data models, Faces, Imaging, 3D, Face Models
BibRef
Wang, N.X.[Nan-Xi],
Wang, Z.Y.[Zhong-Yuan],
He, Z.[Zheng],
Huang, B.J.[Bao-Jin],
Zhou, L.G.[Li-Guo],
Han, Z.[Zhen],
A Tilt-Angle Face Dataset and Its Validation,
ICIP21(894-898)
IEEE DOI
2201
Training, Deep learning, Solid modeling, Image recognition,
Face recognition, Video surveillance, Face dataset, overhead view,
face recognition
BibRef
Li, P.Y.[Peng-Yu],
Wang, B.[Biao],
Zhang, L.[Lei],
Virtual Fully-Connected Layer: Training a Large-Scale Face
Recognition Dataset with Limited Computational Resources,
CVPR21(13310-13319)
IEEE DOI
2111
Training, Measurement, Codes, Face recognition,
Memory management, Graphics processing units
BibRef
Liang, J.[Jie],
Zeng, H.[Hui],
Cui, M.M.[Miao-Miao],
Xie, X.S.[Xuan-Song],
Zhang, L.[Lei],
PPR10K: A Large-Scale Portrait Photo Retouching Dataset with
Human-Region Mask and Group-Level Consistency,
CVPR21(653-661)
IEEE DOI
2111
Photography, Visualization, Codes,
Computational modeling, Task analysis
BibRef
Xu, X.K.[Xing-Kun],
Huang, Y.[Yuge],
Shen, P.C.[Peng-Cheng],
Li, S.X.[Shao-Xin],
Li, J.L.[Ji-Lin],
Huang, F.Y.[Fei-Yue],
Li, Y.[Yong],
Cui, Z.[Zhen],
Consistent Instance False Positive Improves Fairness in Face
Recognition,
CVPR21(578-586)
IEEE DOI
2111
Training, Codes, Annotations, Face recognition, Benchmark testing
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Tong, L.[Liang],
Chen, Z.Z.[Zheng-Zhang],
Ni, J.C.[Jing-Chao],
Cheng, W.[Wei],
Song, D.J.[Dong-Jin],
Chen, H.F.[Hai-Feng],
Vorobeychik, Y.[Yevgeniy],
FACESEC:
A Fine-grained Robustness Evaluation Framework for Face Recognition Systems,
CVPR21(13249-13258)
IEEE DOI
2111
Systematics, Face recognition,
Perturbation methods, Neural networks, Training data, Computer architecture
BibRef
Poster, D.[Domenick],
Thielke, M.[Matthew],
Nguyen, R.[Robert],
Rajaraman, S.[Srinivasan],
Di, X.[Xing],
Fondje, C.N.[Cedric Nimpa],
Patel, V.M.[Vishal M.],
Short, N.J.[Nathaniel J.],
Riggan, B.S.[Benjamin S.],
Nasrabadi, N.M.[Nasser M.],
Hu, S.[Shuowen],
A Large-Scale, Time-Synchronized Visible and Thermal Face Dataset,
WACV21(1558-1567)
IEEE DOI
PDF File.
2106
Dataset, Face Recognition. Heating systems, Protocols, Thermal lensing, Photothermal effects,
Cameras, Thermal analysis, Task analysis
BibRef
Balazia, M.[Michal],
Happy, S.L.[S L],
Brémond, F.[François],
Dantcheva, A.[Antitza],
How Unique Is a Face: An Investigative Study,
ICPR21(7066-7071)
IEEE DOI
2105
Image resolution, Protocols, Databases, Face recognition, Banking,
Feature extraction, Entropy
BibRef
Greco, A.[Antonio],
Saggese, A.[Alessia],
Vento, M.[Mario],
Vigilante, V.[Vincenzo],
Performance Assessment of Face Analysis Algorithms with Occluded Faces,
DEEPRETAIL20(472-486).
Springer DOI
2103
BibRef
Guo, Z.,
The development and comparison of face recognition algorithms based
on different technical characteristics,
CVIDL20(6-10)
IEEE DOI
2102
convolutional neural nets, face recognition,
image matching, human face,
YOLO
BibRef
Jiang, E.,
A review of the comparative studies on traditional and intelligent
face recognition methods,
CVIDL20(11-15)
IEEE DOI
2102
face recognition, feature extraction, image representation,
learning (artificial intelligence), statistical analysis,
Deep learning
BibRef
Williford, J.R.[Jonathan R.],
May, B.B.[Brandon B.],
Byrne, J.[Jeffrey],
Explainable Face Recognition,
ECCV20(XI:248-263).
Springer DOI
2011
Explain why the match was returned.
BibRef
Wang, P.,
Wang, Z.,
Ji, Z.,
Liu, X.,
Yang, S.,
Wu, Z.,
TAL EmotioNet Challenge 2020 Rethinking the Model Chosen Problem in
Multi-Task Learning,
EmotioNet20(1653-1656)
IEEE DOI
2008
Training, Noise measurement, Face recognition, Face, Data models, Optimization
BibRef
Yang, H.,
Zhu, H.,
Wang, Y.,
Huang, M.,
Shen, Q.,
Yang, R.,
Cao, X.,
FaceScape: A Large-Scale High Quality 3D Face Dataset and Detailed
Riggable 3D Face Prediction,
CVPR20(598-607)
IEEE DOI
2008
Face, Solid modeling, Shape, Geometry,
Predictive models, Cameras
BibRef
Albiero, V.[Vítor],
Krishnapriya, K.S.,
Vangara, K.[Kushal],
Zhang, K.[Kai],
King, M.C.[Michael C.],
Bowyer, K.W.[Kevin W.],
Analysis of Gender Inequality In Face Recognition Accuracy,
WACVWS20(81-89)
IEEE DOI
2006
Face recognition, Face, Machine learning, Forehead, Training data, Databases
BibRef
Bruveris, M.,
Mortazavian, P.,
Gietema, J.,
Mahadevan, M.,
Reducing Geographic Performance Differentials for Face Recognition,
WACVWS20(98-106)
IEEE DOI
2006
Face recognition, Training, Data models, Face, Training data,
Security, Data mining
BibRef
Deng, J.,
Guo, J.,
Zhang, D.,
Deng, Y.,
Lu, X.,
Shi, S.,
Lightweight Face Recognition Challenge,
LFR19(2638-2646)
IEEE DOI
2004
convolutional neural nets, face recognition,
image sensors, large-scale datasets, extensive comparison metric,
lightweight face recognition
BibRef
Bagrov, N.U.,
Konushin, A.S.,
Konushin, V.S.,
Face Recognition With Low False Positive Error Rate,
PTVSBB19(11-15).
DOI Link
1912
BibRef
Xu, X.,
Kakadiaris, I.A.,
FaRE: Open Source Face Recognition Performance Evaluation Package,
ICIP19(3272-3276)
IEEE DOI
1910
Code, Face Recognition. Face Recognition, Evaluation, Toolbox
BibRef
Dhar, P.[Prithviraj],
Castillo, C.[Carlos],
Chellappa, R.[Rama],
On Measuring the Iconicity of a Face,
WACV19(2137-2145)
IEEE DOI
1904
For a given face, some in the database are more representative that the
others.
face recognition, feature extraction, multilayer perceptrons,
face dataset, iconic images, face image, iconicity scores,
Task analysis
BibRef
Gallo, I.,
Nawaz, S.,
Calefati, A.,
Piccoli, G.,
A Pipeline to Improve Face Recognition Datasets and Applications,
IVCNZ18(1-6)
IEEE DOI
1902
Videos, Face, Pipelines, Face recognition, Clustering algorithms,
Cleaning, YouTube, face recognition, convolutional neural network,
cleaning dataset
BibRef
Akbir, K.,
Mahmoud, M.,
Considering Race a Problem of Transfer Learning,
DVPBA19(100-106)
IEEE DOI
1902
Task analysis, Image generation, Hair,
Benchmark testing, Biological system modeling, Training
BibRef
Nguyen, V.,
Tran, M.,
Luo, J.,
Are French Really That Different? Recognizing Europeans from Faces
Using Data-Driven Learning,
ICPR18(2729-2734)
IEEE DOI
1812
Facial features, Twitter, Europe, Neural networks, Sociology,
Statistics, Training
BibRef
Ferrari, C.,
Berretti, S.[Stefano],
del Bimbo, A.[Alberto],
Extended YouTube Faces:
A Dataset for Heterogeneous Open-Set Face Identification,
ICPR18(3408-3413)
IEEE DOI
1812
Face, Protocols, Face recognition, Videos, Probes, Benchmark testing, Media
See also YouTube Faces DB.
BibRef
Zhong, Y.,
Deng, W.,
Deep Difference Analysis in Similar-looking Face recognition,
ICPR18(3353-3358)
IEEE DOI
1812
Face, Heating systems, Visualization, Face recognition,
Feature extraction, Databases, Task analysis
BibRef
Martínez-Díaz, Y.,
Méndez-Vázquez, H.,
López-Avila, L.,
Chang, L.,
Sucar, L.E.,
Tistarelli, M.[Massimo],
Toward More Realistic Face Recognition Evaluation Protocols for the
YouTube Faces Database,
Biometrics18(526-5268)
IEEE DOI
1812
Videos, Face, Protocols, Databases, Face recognition, Measurement, Standards
See also YouTube Faces DB.
BibRef
de Castro, D.C.[Daniel Coelho],
Nowozin, S.[Sebastian],
From Face Recognition to Models of Identity: A Bayesian Approach to
Learning About Unknown Identities from Unsupervised Data,
ECCV18(II: 764-780).
Springer DOI
1810
BibRef
Xie, W.D.[Wei-Di],
Shen, L.[Li],
Zisserman, A.[Andrew],
Comparator Networks,
ECCV18(XI: 811-826).
Springer DOI
1810
decide if two sets of images of a face are of the same person or not.
BibRef
Wang, F.[Fei],
Chen, L.[Liren],
Li, C.[Cheng],
Huang, S.[Shiyao],
Chen, Y.J.[Yan-Jie],
Qian, C.[Chen],
Loy, C.C.[Chen Change],
The Devil of Face Recognition Is in the Noise,
ECCV18(IX: 780-795).
Springer DOI
1810
BibRef
Liu, X.F.[Xiao-Feng],
Vijaya Kumar, B.V.K.,
Yang, C.[Chao],
Tang, Q.M.[Qing-Ming],
You, J.[Jane],
Dependency-Aware Attention Control for Unconstrained Face Recognition
with Image Sets,
ECCV18(XI: 573-590).
Springer DOI
1810
BibRef
Cao, J.,
Li, Y.,
Zhang, Z.,
Celeb-500K: A Large Training Dataset for Face Recognition,
ICIP18(2406-2410)
IEEE DOI
1809
Dataset, Face Recognition. Training, Face, Face recognition, Measurement, Learning systems,
Performance gain, Face detection, face recognition, face dataset,
convolutional neural networks
BibRef
Peng, B.,
Yang, H.,
Li, D.,
Zhang, Z.,
An Empirical Study of Face Recognition under Variations,
FG18(310-317)
IEEE DOI
1806
Distortion, Face, Feature extraction, Image coding, Lighting,
Deep learning, Face Recognition, Handcrafted feature
BibRef
Banerjee, S.,
Brogan, J.,
Krizaj, J.,
Bharati, A.,
Webster, B.R.,
Struc, V.,
Flynn, P.J.,
Scheirer, W.J.,
To Frontalize or Not to Frontalize: Do We Really Need Elaborate
Pre-processing to Improve Face Recognition?,
WACV18(20-29)
IEEE DOI
1806
face recognition, feedforward neural nets,
learning (artificial intelligence), CNNs,
BibRef
Nech, A.,
Kemelmacher-Shlizerman, I.,
Level Playing Field for Million Scale Face Recognition,
CVPR17(3406-3415)
IEEE DOI
1711
Benchmark testing, Clustering algorithms, Face, Face recognition,
Flickr, Labeling, Training
BibRef
Whitelam, C.,
Taborsky, E.,
Blanton, A.,
Maze, B.,
Adams, J.,
Miller, T.,
Kalka, N.,
Jain, A.K.,
Duncan, J.A.,
Allen, K.,
Cheney, J.,
Grother, P.,
IARPA Janus Benchmark-B Face Dataset,
Biometrics17(592-600)
IEEE DOI
1709
Dataset, Faces. Benchmark testing, Face, Face detection, Face recognition, Media,
Protocols, Videos
See also IARPA Janus Benchmark A (IJB-A) dataset.
BibRef
Hassanpour, N.[Negar],
Chen, L.[Liang],
A Quantum Probability Inspired Framework for Image-Set Based Face
Identification,
FG17(551-557)
IEEE DOI
1707
Face, Hilbert space, Quantum computing, Quantum mechanics, Silicon, Uncertainty
BibRef
Phillips, P.J.[P. Jonathon],
A Cross Benchmark Assessment of a Deep Convolutional Neural Network
for Face Recognition,
FG17(705-710)
IEEE DOI
1707
Algorithm design and analysis, Benchmark testing, Face,
Face recognition, Lighting, NIST, Partitioning, algorithms
BibRef
Zuo, H.,
Wang, L.,
Qin, J.,
XJU1: A Chinese Ethnic Minorities Face Database,
CMVIT17(7-11)
IEEE DOI
1704
face recognition
BibRef
Gilani, S.Z.[Syed Zulqarnain],
Mian, A.S.[Ajmal S.],
Towards Large-Scale 3D Face Recognition,
DICTA16(1-8)
IEEE DOI
1701
Databases. Recognition rates drop as size of dataset increases.
BibRef
Gorodnichy, D.O.[Dmitry O.],
Bissessar, D.[David],
Granger, E.[Eric],
Laganiére, R.[Robert],
Recognizing People and Their Activities in Surveillance Video:
Technology State of Readiness and Roadmap,
CRV16(250-259)
IEEE DOI
1612
Face
BibRef
Escalera, S.,
Torres, M.T.,
Martínez, B.,
Baró, X.,
Escalante, H.J.,
Guyon, I.,
Tzimiropoulos, G.[Georgios],
Corneanu, C.A.,
Oliu Simón, M.[Marc],
Bagheri, M.A.,
Valstar, M.,
ChaLearn Looking at People and Faces of the World:
Face Analysis Workshop and Challenge 2016,
ChaLearn16(706-713)
IEEE DOI
1612
BibRef
de Freitas Pereira, T.[Tiago],
Marcel, S.[Sebastien],
Heterogeneous Face Recognition Using Inter-Session Variability
Modelling,
Biometrics16(179-186)
IEEE DOI
1612
BibRef
Adams, J.C.,
Allen, K.C.,
Miller, T.,
Kalka, N.D.[Nathan D.],
Jain, A.K.,
Grouper: Optimizing Crowdsourced Face Annotations,
Biometrics16(163-170)
IEEE DOI
1612
BibRef
Kemelmacher-Shlizerman, I.,
Seitz, S.M.,
Miller, D.,
Brossard, E.,
The MegaFace Benchmark: 1 Million Faces for Recognition at Scale,
CVPR16(4873-4882)
IEEE DOI
1612
Dataset, Face Recognition.
BibRef
Zhan, X.H.[Xiao-Hang],
Pan, X.G.[Xin-Gang],
Liu, Z.W.[Zi-Wei],
Lin, D.[Dahua],
Loy, C.C.[Chen Change],
Self-Supervised Learning via Conditional Motion Propagation,
CVPR19(1881-1889).
IEEE DOI
2002
BibRef
Zhan, X.H.[Xiao-Hang],
Liu, Z.W.[Zi-Wei],
Yan, J.J.[Jun-Jie],
Lin, D.H.[Da-Hua],
Loy, C.C.[Chen Change],
Consensus-Driven Propagation in Massive Unlabeled Data for Face
Recognition,
ECCV18(IX: 576-592).
Springer DOI
1810
BibRef
Li, Y.N.[Yi-Ning],
Huang, C.[Chen],
Loy, C.C.[Chen Change],
Tang, X.[Xiaoou],
Human Attribute Recognition by Deep Hierarchical Contexts,
ECCV16(VI: 684-700).
Springer DOI
1611
See also WIDER Attribute dataset.
BibRef
Guo, Y.D.[Yan-Dong],
Zhang, L.[Lei],
Hu, Y.X.[Yu-Xiao],
He, X.D.[Xiao-Dong],
Gao, J.F.[Jian-Feng],
MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition,
ECCV16(III: 87-102).
Springer DOI
1611
Dataset, Face Recognition.
WWW Link.
BibRef
Fedorovf, I.[Igor],
Giri, R.[Ritwik],
Rao, B.D.[Bhaskar D.],
Nguyen, T.Q.[Truong Q.],
Robust Bayesian method for simultaneous block sparse signal recovery
with applications to face recognition,
ICIP16(3872-3876)
IEEE DOI
1610
Bayes methods
BibRef
Iliadis, M.[Michael],
Spinoulas, L.[Leonidas],
Berahas, A.S.[Albert S.],
Wang, H.H.[Hao-Hong],
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Misevic, D.,
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And:
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1005
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1311
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Giorgi, D.,
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Falcidieno, B.,
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Rakshit, R.D.[Rinku Datta],
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Face Identification Using Local Ternary Tree Pattern Based Spatial
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IbPRIA19(II:50-63).
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1910
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Kisku, D.R.[Dakshina R.],
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Martínez-Contreras, F.[Francisco],
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IbPRIA09(338-345).
Springer DOI
0906
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Franco, A.[Annalisa],
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Maltoni, D.[Davide],
The Big Brother Database:
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ICB09(142-150).
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0906
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Poh, N.[Norman],
Chan, C.H.[Chi Ho],
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Marcel, S.[Sébastien],
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Castro, J.L.A.[José Luis Alba],
Villegas, M.[Mauricio],
Paredes, R.[Roberto],
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Paveic, N.[Nikola],
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Je, H.M.[Hong-Mo],
Jun, B.J.[Bong-Jin],
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0809
See also POSTECH Face Database.
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Huang, G.B.[Gary B.],
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0810
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Nik, M.A.[Melika Abbasian],
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0712
Dataset, Faces.
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Gao, X.F.[Xiu-Feng],
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ICB07(242-251).
Springer DOI
0708
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Müller, M.K.[Marco K.],
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Tewes, A.H.J.[Andreas H. J.],
Schäfer, A.[Achim],
Würtz, R.P.[Rolf P.],
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Springer DOI
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Ho, W.H.[Wai Han],
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CAIP07(351-359).
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MCAM07(343-350).
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0706
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Ho, W.H.[Wai Han],
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A New Performance Evaluation Method for Face Identification:
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CVPR07(1-6).
IEEE DOI
0706
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Ho, W.H.[Wai Han],
Watters, P.[Paul],
Verity, D.[Dominic],
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ICPR06(III: 1155-1160).
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0606
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Aggarwal, G.,
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UMD Experiments with FRGC Data,
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0507
BibRef
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Pesenti, B.,
Tsaregorodtsev, A.,
West, D.,
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IEEE DOI
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0604
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0910
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IEEE DOI
0809
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Ekenel, H.K.,
Pnevmatikakis, A.,
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0604
CHIL: Computers in the Human Interaction Loop
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Messer, K.[Kieron],
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IEEE DOI
0206
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And:
EEMCV01(xx-yy).
0110
See also Meta-Analysis of Third-Party Evaluations of Iris Recognition.
BibRef
Denes, L.J.,
Metes, P.,
Liu, Y.,
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CMU-RI-TR-02-25, October, 2002.
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Dataset, Faces.
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Liu, X.M.[Xiao-Ming],
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Geometry-assisted statistical modeling for face mosaicing,
ICIP03(II: 883-886).
IEEE DOI
0312
BibRef
Qidwai, S.[Saim],
Venkataramani, K.[Krithika],
Gutta, S.[Srinivas],
Wechsler, H.[Harry],
Face Recognition Using Asymmetric Faces,
ICBA04(162-168).
Springer DOI
0505
BibRef
Gutta, S.[Srinivas],
Wechsler, H.[Harry],
Partial Faces for Face Recognition: Left vs Right Half,
CAIP03(630-637).
Springer DOI
0311
BibRef
Gutta, S.,
Philomin, V.,
Trajkovic, M.,
An investigation into the use of partial-faces for face recognition,
AFGR02(28-33).
IEEE DOI
0206
BibRef
Yacoob, Y.,
Davis, L.S.,
Smiling faces are better for face recognition,
AFGR02(52-57).
IEEE DOI
0206
BibRef
Gutta, S.[Srinivas],
Huang, J.[Jeffrey],
Liu, C.J.[Cheng-Jun],
Wechsler, H.[Harry],
Comparative Performance Evaluation of Gray-Scale and Color Information
for Face Recognition Tasks,
AVBPA01(38).
Springer DOI
0310
BibRef
Bigun, J.[Josef],
Choy, K.W.[Kwok-Wai],
Olsson, H.[Henrik],
Evidence on Skill Differences of Women and Men Concerning Face
Recognition,
AVBPA01(44).
Springer DOI
0310
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Kosmerlj, M.[Marijana],
Fladsrud, T.[Tom],
Hjelmĺs, E.[Erik],
Snekkenes, E.[Einar],
Face Recognition Issues in a Border Control Environment,
ICB06(33-39).
Springer DOI
0601
BibRef
Hjelmĺs, E.[Erik],
Farup, I.[Ivar],
A Comparison of Face/Non-face Classifiers,
AVBPA01(65).
Springer DOI
0310
BibRef
Wallhoff, F.,
Eickeler, S.,
Rigoll, G.,
A Comparison of Discrete and Continuous Output Modeling Techniques for
a Pseudo-2d Hidden Markov Model Face Recognition System,
ICIP01(II: 685-688).
IEEE DOI
0108
BibRef
Eickeler, S.[Stefan],
Jabs, M.[Mirco],
Rigoll, G.[Gerhard],
Comparison of Confidence Measures for Face Recognition,
AFGR00(257-262).
IEEE DOI
0003
BibRef
Alvira, M.[Mariano],
Rifkin, R.[Ryan],
An Empirical Comparison of SNoW and SVMs for Face Detection,
MIT AI Memo-2001-004, January 2001.
WWW Link.
0105
BibRef
Varsta, M.,
Heikkonen, J.,
Millán, J.D.R.[Jose Del R.],
Mourińo, J.,
Evaluating the Performance of Three Feature Sets for Brain-computer
Interfaces with an Early Stopping MLP Committee,
ICPR00(Vol II: 907-910).
IEEE DOI
0009
BibRef
Sukthankar, G.,
Face Recognition: A Critical Look at Biologically-Inspired Approaches,
CMU-RI-TR-00-04, January, 2000.
PDF File.
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0001
Bruce, V.[Vicki],
Burton, A.M.[A. Mike],
Hancock, P.J.B.[Peter J.B.],
Comparisons between Human and Computer Recognition of Faces,
AFGR98(408-413).
IEEE DOI
BibRef
9800
Li, S.Z.,
Lu, J.,
Generalizing Capacity of Face Database for Face Recognition,
AFGR98(402-406).
IEEE DOI
BibRef
9800
Nakatsu, R.[Ryohei],
Nonverbal Information Recognition and Its Application to Communications,
AFGR98(2-7).
IEEE DOI
BibRef
9800
Loui, A.C.,
Judice, C.N.,
Liu, S.[Sheng],
An image database for benchmarking of automatic face detection and
recognition algorithms,
ICIP98(I: 146-150).
IEEE DOI
9810
BibRef
Ramsay, C.S.,
Sutherland, K.,
Renshaw, D.,
Denyer, P.B.,
A Comparison of Vector Quantization Codebook Generation Algorithms
Applied to Automatic Face Recognition,
BMVC92(xx-yy).
PDF File.
9209
BibRef
Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Face Verification, Authentication, Evaluations, Verification Benchmarks .