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Topic · Computer Vision and Pattern Recognition

Generative Adversarial Networks and Image Synthesis

Generative Adversarial Networks and Image Synthesis is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 19k 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 Generative Adversarial Networks (GANs) in image processing, including image synthesis, style transfer, representation learning, and unsupervised learning. The papers cover various techniques such as image inpainting, texture synthesis, and conditional generative models using deep learning and neural networks.

  • Generative Adversarial Networks
  • Image Synthesis
  • Deep Learning
  • Neural Networks
  • Image Inpainting
  • Style Transfer
  • Representation Learning
  • Unsupervised Learning
  • Conditional Generative Models
  • Texture Synthesis
Research works
19k
fractional, since 1951
In the world top 10%
3.5k
per year above
Top-10% rate
18.5%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+350%
the tick is no change

Which countries lead Generative Adversarial Networks and Image Synthesis research?

By volume, China and India publish the most (3.3k and 1k works in 2022–2025).

By volume, 2022–2025

  1. 1 China 3.3k works
  2. 2 India 1k works
  3. 3 United States 1k works
  4. 4 South Korea 344 works
  5. 5 United Kingdom 283 works
  6. 6 Japan 253 works
  7. 7 Germany 241 works
  8. 8 France 158 works
  9. 9 Canada 148 works
  10. 10 Italy 146 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: 47.9%India: 14.8%United States: 14.6%South Korea: 5.0%6 others listed: 17.7%48%largest
China3,317 · 47.9%India1,027 · 14.8%United States1,011 · 14.6%South Korea344 · 5.0%6 others listed1,228 · 17.7%

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

Which institutions lead Generative Adversarial Networks and Image Synthesis research?

By volume in 2022–2025, Shanghai Jiao Tong University publishes the most Generative Adversarial Networks and Image Synthesis research, followed by Tsinghua University and Zhejiang University.

By volume, 2022–2025

  1. 1 Shanghai Jiao Tong UniversityChina 76 works
  2. 2 Tsinghua UniversityChina 67 works
  3. 3 Zhejiang UniversityChina 65 works
  4. 4 University of Science and Technology of ChinaChina 64 works
  5. 5 Beijing University of Posts and TelecommunicationsChina 50 works
  6. 6 Chinese Academy of SciencesChina 50 works
  7. 7 Sun Yat-sen UniversityChina 48 works
  8. 8 Peking UniversityChina 45 works
  9. 9 Fudan UniversityChina 42 works
  10. 10 Nanyang Technological UniversitySingapore 42 works

Who are the leading researchers in Generative Adversarial Networks and Image Synthesis?

The most-cited researchers publishing on Generative Adversarial Networks and Image Synthesis include Andrew Zisserman, Karen Simonyan and Geoffrey E. Hinton.

  1. 1 Andrew Zisserman United Kingdom 25k citations
  2. 2 Karen Simonyan United States 23k citations
  3. 3 Geoffrey E. Hinton Canada 22k citations
  4. 4 Ilya Sutskever United States 21k citations
  5. 5 Dumitru Erhan United States 17k citations
  6. 6 Kaiming He Israel 17k citations
  7. 7 Yoshua Bengio Canada 17k citations
  8. 8 Serge Belongie United States 14k citations
  9. 9 Xiaogang Wang Russia 13k citations
  10. 10 Jitendra Malik United States 12k citations

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

Where is Generative Adversarial Networks and Image Synthesis research done?

The largest centres of Generative Adversarial Networks and Image Synthesis research in 2022–2025 are Beijing (China), Shanghai (China), Seoul (South Korea) and Hangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in San Jose, Greater Noida and Mountain View.

Largest cities, 2022–2025

  1. 1 Beijing China 675 works
  2. 2 Shanghai China 285 works
  3. 3 Seoul South Korea 173 works
  4. 4 Hangzhou China 173 works
  5. 5 Xi'an China 172 works
  6. 6 Guangzhou China 164 works
  7. 7 Nanjing China 151 works
  8. 8 Shenzhen China 151 works
  9. 9 Wuhan China 145 works
  10. 10 Hong Kong China 113 works

Where it is the local speciality

  1. San JoseUS · 30.5 works11×
  2. Greater NoidaIN · 30.2 works5.7×
  3. Mountain ViewUS · 26.0 works5.5×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Generative Adversarial Networks and Image Synthesis than the world average.

See Generative Adversarial Networks and Image Synthesis on the map

Where is the best place to study Generative Adversarial Networks and Image Synthesis?

Among universities, judged by research, Nanyang Technological University, Hong Kong University of Science and Technology and Korea Advanced Institute of Science and Technology 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%60%mean 29.61%fractional works in this node (log) →share in the world top 10% →Nanyang Technological University: 42, 35.7%Hong Kong University of Science and Technology: 23, 34.8%Korea Advanced Institute of Science and Technology: 34, 21.2%University of Science and Technology of China: 64, 22.6%Tel Aviv University: 16, 53.8%University of Hong Kong: 26, 34.2%Communication University of China: 21, 21.3%Tsinghua University: 67, 28.8%Carnegie Mellon University: 21, 35.9%Beijing University of Posts and Telecommunications: 50, 7.8%Nanyang Technologica…Hong Kong University…University of Scienc…Korea Advanced Insti…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Nanyang Technological UniversitySingapore 72.435.7%6.3×42 +196.6%
2 Hong Kong University of Science and TechnologyHong Kong 69.334.8%6.9×23 +492.5%
3 Korea Advanced Institute of Science and TechnologySouth Korea 63.521.2%8.6×34 +1094.8%
4 University of Science and Technology of ChinaChina 63.222.6%6.3×64 +384.1%
5 Tel Aviv UniversityIsrael 63.153.8%3.6×16 +275.3%
6 University of Hong KongHong Kong 61.534.2%3.7×26 +249.6%
7 Communication University of ChinaChina 61.421.3%24.0×21 +239.6%
8 Tsinghua UniversityChina 61.328.8%4.0×67 +336.7%
9 Carnegie Mellon UniversityUnited States 61.335.9%6.2×21 +1049.8%
10 Beijing University of Posts and TelecommunicationsChina 60.97.8%9.7×50 +842.1%

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 Generative Adversarial Networks and Image Synthesis research growing?

Output in 2018–2022 was 350% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Generative Adversarial Networks and Image Synthesis.

19801990200020102020
grewheldshrank

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.