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Topic · Computer Vision and Pattern Recognition

Face and Expression Recognition

Face and Expression Recognition is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 42k research works in it since 1951. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of various machine learning and dimensionality reduction techniques to the field of face recognition. It covers topics such as feature selection, support vector machines, ensemble methods, local binary patterns, non-negative matrix factorization, spectral clustering, Laplacian eigenmaps, and sparse representation in the context of face recognition.

  • Face Recognition
  • Dimensionality Reduction
  • Feature Selection
  • Support Vector Machines
  • Ensemble Methods
  • Local Binary Patterns
  • Non-negative Matrix Factorization
  • Spectral Clustering
  • Laplacian Eigenmaps
  • Sparse Representation
Research works
42k
fractional, since 1951
In the world top 10%
4.1k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+8%
the tick is no change
Largest producer
China
52% of the 10 largest, 2022-now
Face and Expression Recognition

Which countries lead Face and Expression Recognition research?

By volume, China and India publish the most (3.7k and 1.7k works in 2022-now).

By volume, 2022-now

  1. 1 China 3.7k works
  2. 2 India 1.7k works
  3. 3 United States 628 works
  4. 4 Indonesia 187 works
  5. 5 Japan 180 works
  6. 6 South Korea 170 works
  7. 7 United Kingdom 147 works
  8. 8 Iran 146 works
  9. 9 ?? 133 works
  10. 10 Iraq 130 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: 52.3%India: 23.5%United States: 8.8%Indonesia: 2.6%6 others listed: 12.8%52%largest
China3,717 · 52.3%India1,668 · 23.5%United States628 · 8.8%Indonesia187 · 2.6%6 others listed907 · 12.8%

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

Which institutions lead Face and Expression Recognition research?

By volume in 2022-now, Chinese Academy of Sciences publishes the most Face and Expression Recognition research, followed by Xidian University and Saveetha University.

By volume, 2022-now

  1. 1 Chinese Academy of SciencesChina 79 works
  2. 2 Xidian UniversityChina 77 works
  3. 3 Saveetha UniversityIndia 73 works
  4. 4 Northwestern Polytechnical UniversityChina 70 works
  5. 5 SRM Institute of Science and TechnologyIndia 54 works
  6. 6 National University of Defense TechnologyChina 51 works
  7. 7 University of Electronic Science and Technology of ChinaChina 44 works
  8. 8 Shenzhen UniversityChina 43 works
  9. 9 Guangdong University of TechnologyChina 41 works
  10. 10 Xi'an Jiaotong UniversityChina 41 works

Who are the leading researchers in Face and Expression Recognition?

The most-cited researchers publishing on Face and Expression Recognition include Yoshua Bengio, Geoffrey E. Hinton and Robert John Tibshirani.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Geoffrey E. Hinton Canada 454k citations
  3. 3 Robert John Tibshirani United States 396k citations
  4. 4 Shaoqing Ren China 356k citations
  5. 5 Trevor Hastie United States 301k citations
  6. 6 Jian Sun 281k citations
  7. 7 Charles M. Perou United States 263k citations
  8. 8 Xiaogang Wang China 260k citations
  9. 9 Yann LeCun United States 256k citations
  10. 10 Andrew Zisserman United Kingdom 255k 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 and Expression Recognition?

The most cited paper in Face and Expression Recognition is "Random Forests" (Leo Breiman, 2001), with 132,956 citations. Next come "LIBSVM" (41,500) and "Support-vector networks" (41,211).

Most cited papers
#PaperReleasedCitations
1 Random Forests Leo Breiman · Machine Learning Open access Oct 2001 132,956
2 LIBSVM Chih-Chung Chang, Chih‐Jen Lin · ACM Transactions on Intelligent Systems and Technology Apr 2011 41,500
3 Support-vector networks Corinna Cortes, Vladimir N. Vapnik · Machine Learning Open access Sep 1995 41,211
4 Regularization and Variable Selection Via the Elastic Net Hui Jun Zou, Trevor Hastie · Journal of the Royal Statistical Society Series B (Statistical Methodology) Open access 9 Mar 2005 21,757
5 Rapid object detection using a boosted cascade of simple features Paul A. Viola, Michael Jones Conference paper 24 Aug 2005 18,370
All 99 most cited papers, with filters and sorting

Where is Face and Expression Recognition research done?

The largest centres of Face and Expression Recognition research in 2022-now are Beijing (China), Xi'an (China), Chennai (India) and Guangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Vijayawada, Greater Noida and Wuhu.

Largest cities, 2022-now

  1. 1 BeijingChina 487 works
  2. 2 Xi'anChina 301 works
  3. 3 ChennaiIndia 213 works
  4. 4 GuangzhouChina 189 works
  5. 5 NanjingChina 187 works
  6. 6 ShanghaiChina 185 works
  7. 7 WuhanChina 148 works
  8. 8 ChengduChina 147 works
  9. 9 ChongqingChina 126 works
  10. 10 ChangshaChina 118 works

Where it is the local speciality

  1. VijayawadaIN · 46.8 works11×
  2. Greater NoidaIN · 40.4 works7.0×
  3. WuhuCN · 28.0 works6.7×
← less than its size predicts1×more →

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

See Face and Expression Recognition on the map

Where is the best place to study Face and Expression Recognition?

Among universities, judged by research, Northwestern Polytechnical University, China University of Geosciences and Indian Institute of Technology Indore 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 25.46%fractional works in this field (log) →share of work in the world top 10% →Indian Institute of …China University of …Northwestern Polytec…Xidian University
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
1Northwestern Polytechnical UniversityChina 73.228.7%7.8×70 -9.4%
2China University of GeosciencesChina 67.735.6%4.5×16 +67.4%
3Indian Institute of Technology IndoreIndia 66.839.3%11.3×15 +5.5%
4Xidian UniversityChina 66.214.7%13.4×77 +9.8%
5National University of Defense TechnologyChina 64.226.2%8.3×51 -3.0%
6Southwest UniversityChina 58.720.1%7.0×30 +110.8%
7Southwest Jiaotong UniversityChina 58.517.3%5.8×35 +85.7%
8Harbin Institute of TechnologyChina 58.319.6%3.0×39 +31.0%
9Chongqing University of Posts and TelecommunicationsChina 58.016.9%16.2×37 +21.0%
10Nantong UniversityChina 57.636.2%3.0×11 +64.7%

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 and Expression Recognition, country by country

Is Face and Expression Recognition research growing?

Output in 2022-2025 was 8% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Face and Expression Recognition.

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 and Expression Recognition as a percentage of every work published that year, 0.040% in 2024.

still counting0.020%0.040%0.060%Face and Expression Recognition0.039% in 202519801990200020102020

Fractional works of Face and Expression Recognition 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 and Expression Recognition9.9% 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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