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Topic · Computer Vision and Pattern Recognition

Face recognition and analysis

Face recognition and analysis is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 27k research works in it since 1954. 9.8% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on various techniques for face recognition and analysis, including deep learning approaches, facial landmark detection, age estimation, 3D face reconstruction, facial expression analysis, and pose estimation. The papers cover topics such as metric learning, feature learning, and the application of convolutional neural networks to address challenges in face recognition.

  • Face Recognition
  • Facial Landmark Detection
  • Deep Learning
  • Age Estimation
  • 3D Face Reconstruction
  • Facial Expression Analysis
  • Pose Estimation
  • Feature Learning
  • Metric Learning
  • Convolutional Neural Networks
Research works
27k
fractional, since 1954
In the world top 10%
2.7k
per year above
Top-10% rate
9.8%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+59%
the tick is no change
Largest producer
China
40% of the 10 largest, 2022-now
Face recognition and analysis

Which countries lead Face recognition and analysis research?

By volume, China and India publish the most (3.2k and 2.3k works in 2022-now).

By volume, 2022-now

  1. 1 China 3.2k works
  2. 2 India 2.3k works
  3. 3 United States 817 works
  4. 4 Indonesia 293 works
  5. 5 South Korea 282 works
  6. 6 United Kingdom 279 works
  7. 7 Japan 275 works
  8. 8 Germany 205 works
  9. 9 Iraq 165 works
  10. 10 ?? 165 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 40.3%India: 28.6%United States: 10.2%Indonesia: 3.7%6 others listed: 17.2%40%largest
China3,222 · 40.3%India2,283 · 28.6%United States817 · 10.2%Indonesia293 · 3.7%6 others listed1,371 · 17.2%

Shares of the rows listed above, not of the whole node.

Which institutions lead Face recognition and analysis research?

By volume in 2022-now, Chinese Academy of Sciences publishes the most Face recognition and analysis research, followed by Shanghai Jiao Tong University and SRM Institute of Science and Technology.

By volume, 2022-now

  1. 1 Chinese Academy of SciencesChina 117 works
  2. 2 Shanghai Jiao Tong UniversityChina 71 works
  3. 3 SRM Institute of Science and TechnologyIndia 70 works
  4. 4 Vellore Institute of Technology UniversityIndia 57 works
  5. 5 Saveetha UniversityIndia 57 works
  6. 6 University of Science and Technology of ChinaChina 55 works
  7. 7 Tsinghua UniversityChina 52 works
  8. 8 Xidian UniversityChina 48 works
  9. 9 Amrita Vishwa VidyapeethamIndia 47 works
  10. 10 Beijing University of Posts and TelecommunicationsChina 45 works

Who are the leading researchers in Face recognition and analysis?

The most-cited researchers publishing on Face recognition and analysis include Kaiming He, Yoshua Bengio and Geoffrey E. Hinton.

  1. 1 Kaiming He Israel 562k citations
  2. 2 Yoshua Bengio Canada 476k citations
  3. 3 Geoffrey E. Hinton Canada 454k citations
  4. 4 Shaoqing Ren China 356k citations
  5. 5 Xiangyu Zhang 327k citations
  6. 6 Jian Sun 281k citations
  7. 7 Xiaogang Wang China 260k citations
  8. 8 Andrew Zisserman United Kingdom 255k citations
  9. 9 Li Fei-Fei United States 225k citations
  10. 10 Kai You Wang China 224k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Face recognition and analysis?

The most cited paper in Face recognition and analysis is "Eigenfaces for Recognition" (Matthew Turk, Alex Pentland, 1991), with 13,806 citations. Next come "Rectified Linear Units Improve Restricted Boltzmann Machines" (13,220) and "Eigenfaces vs. Fisherfaces: recognition using class specific linear projection" (11,777).

Most cited papers
#PaperReleasedCitations
1 Eigenfaces for Recognition Matthew Turk, Alex Pentland · Journal of Cognitive Neuroscience 1991 13,806
2 Rectified Linear Units Improve Restricted Boltzmann Machines Vinod B Nair, Geoffrey E. Hinton · International Conference on Machine Learning Conference paper 21 Jun 2010 13,220
3 Eigenfaces vs. Fisherfaces: recognition using class specific linear projection Peter N. Belhumeur, João P. Hespanha, David Kriegman · IEEE Transactions on Pattern Analysis and Machine Intelligence Jul 1997 11,777
4 FaceNet: A unified embedding for face recognition and clustering Florian Schroff, Dmitry Kalenichenko, James Philbin Conference paperOpen access Jun 2015 11,581
5 The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception Nancy Kanwisher, Josh H. McDermott, Marvin M. Chun · Journal of Neuroscience Open access Jun 1997 8,016
All 99 most cited papers, with filters and sorting

Where is Face recognition and analysis research done?

The largest centres of Face recognition and analysis research in 2022-now are Beijing (China), Chennai (India), Shanghai (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Martigny-Combe and Pulchowk.

Largest cities, 2022-now

  1. 1 BeijingChina 574 works
  2. 2 ChennaiIndia 270 works
  3. 3 ShanghaiChina 228 works
  4. 4 NanjingChina 167 works
  5. 5 Xi'anChina 162 works
  6. 6 BengaluruIndia 159 works
  7. 7 GuangzhouChina 157 works
  8. 8 WuhanChina 157 works
  9. 9 SeoulSouth Korea 138 works
  10. 10 PuneIndia 136 works

Where it is the local speciality

  1. Martigny-CombeCH · 21.0 works158×
  2. PulchowkNP · 24.5 works12×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Face recognition and analysis than the world average.

See Face recognition and analysis on the map

Where is the best place to study Face recognition and analysis?

Among universities, judged by research, Nanyang Technological University, Hong Kong Polytechnic University and Shanghai Jiao Tong University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 22.97%fractional works in this field (log) →share of work in the world top 10% →Nanyang Technologica…City University of H…Hong Kong Polytechni…Shanghai Jiao Tong U…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Nanyang Technological UniversitySingapore 70.027.5%4.2×30 +53.2%
2Hong Kong Polytechnic UniversityChina 67.122.5%2.6×20 +30.8%
3Shanghai Jiao Tong UniversityChina 66.618.6%2.7×71 +75.4%
4City University of Hong KongChina 65.524.7%3.7×19 +79.0%
5University of Science and Technology of ChinaChina 65.316.9%5.2×55 +52.8%
6Xidian UniversityChina 65.317.3%7.2×48 +32.3%
7Michigan State UniversityUnited States 63.728.4%2.6×17 -0.5%
8Tsinghua UniversityChina 63.219.9%2.5×52 +16.0%
9Technische Universität DarmstadtGermany 63.034.7%3.6×11 +65.7%
10Norwegian University of Science and TechnologyNorway 61.519.2%5.1×26 +199.1%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Face recognition and analysis, country by country

Is Face recognition and analysis research growing?

Output in 2022-2025 was 59% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Face recognition and analysis.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Face recognition and analysis as a percentage of every work published that year, 0.039% in 2024.

still counting0.020%0.040%0.060%Face recognition and analysis0.048% in 202519801990200020102020

Fractional works of Face recognition and analysis over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Face recognition and analysis9.8% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.

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