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. 18.5% 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%
- 7.8k per year above
- Top-10% rate
- 18.5% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +6% the tick is no change
Which countries lead Face and Expression Recognition research?
By volume, China and India publish the most (3.1k and 1.5k works in 2022–2025).
By volume, 2022–2025
- 1 China 3.1k works
- 2 India 1.5k works
- 3 United States 551 works
- 4 Indonesia 179 works
- 5 Japan 159 works
- 6 South Korea 149 works
- 7 United Kingdom 130 works
- 8 Iran 130 works
- 9 Iraq 122 works
- 10 ?? 122 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.
Shares of the rows listed above, not of the whole node.
Which institutions lead Face and Expression Recognition research?
By volume in 2022–2025, Saveetha University publishes the most Face and Expression Recognition research, followed by Xidian University and Northwestern Polytechnical University.
By volume, 2022–2025
- 1 Saveetha University India 71 works
- 2 Xidian University China 67 works
- 3 Northwestern Polytechnical University China 62 works
- 4 National University of Defense Technology China 43 works
- 5 University of Electronic Science and Technology of China China 40 works
- 6 Shenzhen University China 38 works
- 7 SRM Institute of Science and Technology India 37 works
- 8 Guangdong University of Technology China 36 works
- 9 Xi'an Jiaotong University China 35 works
- 10 Harbin Institute of Technology China 34 works
Who are the leading researchers in Face and Expression Recognition?
The most-cited researchers publishing on Face and Expression Recognition include Andrew Zisserman, Yoshua Bengio and Xiaogang Wang.
- 1 Andrew Zisserman 25k citations
- 2 Yoshua Bengio 17k citations
- 3 Xiaogang Wang 13k citations
- 4 Robert Tibshirani 13k citations
- 5 Pietro Perona 11k citations
- 6 Jerome H. Friedman 11k citations
- 7 Wei Liu 9.7k citations
- 8 Chih‐Jen Lin 9.6k citations
- 9 Luc Van Gool 8.5k citations
- 10 Alan Yuille 8.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Face and Expression Recognition research done?
The largest centres of Face and Expression Recognition research in 2022–2025 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, 2022–2025
Where it is the local speciality
- VijayawadaIN · 44.3 works12×
- Greater NoidaIN · 37.0 works7.5×
- WuhuCN · 25.4 works7.1×
Location quotient: how much more of its research is in Face and Expression Recognition than the world average.
Where is the best place to study Face and Expression Recognition?
Among universities, judged by research, Indian Institute of Technology Indore, Northwestern Polytechnical University and Xidian 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.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Indian Institute of Technology Indore India | 74.3 | 50.6% | 10.1× | 14 | +156.4% |
| 2 | Northwestern Polytechnical University China | 66.2 | 35.2% | 6.9× | 62 | +87.1% |
| 3 | Xidian University China | 64.3 | 20.8% | 11.6× | 67 | +49.6% |
| 4 | University of Macau Macau | 62.4 | 29.4% | 6.3× | 16 | +177.3% |
| 5 | National University of Defense Technology China | 58.6 | 32.8% | 7.1× | 43 | +53.7% |
| 6 | Chongqing University of Posts and Telecommunications China | 57.8 | 22.8% | 13.9× | 31 | +44.0% |
| 7 | Shenzhen University China | 57.2 | 18.4% | 6.5× | 38 | +164.5% |
| 8 | Xi’an University of Posts and Telecommunications China | 56.9 | 8.2% | 17.8× | 29 | +207.7% |
| 9 | Guangdong University of Technology China | 55.9 | 18.4% | 8.3× | 36 | +99.8% |
| 10 | Anhui Polytechnic University China | 53.9 | 22.4% | 20.0× | 20 | +56.9% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Face and Expression Recognition research growing?
Output in 2018–2022 was 6% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Face and Expression Recognition.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
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.