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Image Processing and 3D Reconstruction

Image Processing and 3D Reconstruction is a research topic within Computer Vision and Pattern Recognition. Science Explorer counts 29k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the automated reconstruction of fragmented objects, including archaeological artifacts, pottery, and shredded documents. It involves techniques such as image matching, jigsaw puzzle solving, 3D scanning, and computerized classification to reassemble and analyze fragmented cultural heritage objects.

  • Reconstruction
  • Fragmented Objects
  • Archaeological Artifacts
  • Jigsaw Puzzles
  • 3D Scanning
  • Cultural Heritage
  • Image Matching
  • Pottery Analysis
  • Document Reconstruction
  • Computerized Classification
Research works
29k
fractional, since 1950
In the world top 10%
2.9k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+50%
the tick is no change
Largest producer
China
47% of the 10 largest, 2022-now
Image Processing and 3D Reconstruction

Which countries lead Image Processing and 3D Reconstruction research?

By volume, China and the United States publish the most (2.2k and 625 works in 2022-now).

By volume, 2022-now

  1. 1 China 2.2k works
  2. 2 United States 625 works
  3. 3 India 507 works
  4. 4 Germany 263 works
  5. 5 Russia 230 works
  6. 6 France 204 works
  7. 7 Italy 199 works
  8. 8 United Kingdom 186 works
  9. 9 Japan 171 works
  10. 10 Indonesia 123 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: 46.6%United States: 13.3%India: 10.8%Germany: 5.6%6 others listed: 23.7%47%largest
China2,186 · 46.6%United States625 · 13.3%India507 · 10.8%Germany263 · 5.6%6 others listed1,113 · 23.7%

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

Which institutions lead Image Processing and 3D Reconstruction research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Image Processing and 3D Reconstruction research, followed by Chinese Academy of Sciences and Russian Academy of Sciences.

Who are the leading researchers in Image Processing and 3D Reconstruction?

The most-cited researchers publishing on Image Processing and 3D Reconstruction 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 Xiangyu Zhang 327k citations
  5. 5 Trevor Hastie United States 301k citations
  6. 6 Xiaogang Wang China 260k citations
  7. 7 Yann LeCun United States 256k 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 Image Processing and 3D Reconstruction?

The most cited paper in Image Processing and 3D Reconstruction is "Gradient-based learning applied to document recognition" (Yann LeCun, Léon Bottou, Yoshua Bengio et al., 1998), with 59,921 citations. Next come "A method for registration of 3-D shapes" (18,308) and "Bayesian Analysis of Radiocarbon Dates" (8,832).

Most cited papers
#PaperReleasedCitations
1 Gradient-based learning applied to document recognition Yann LeCun, Léon Bottou, Yoshua Bengio et al. · Proceedings of the IEEE Open access 1998 59,921
2 A method for registration of 3-D shapes Paul J. Besl, Neil David McKay · IEEE Transactions on Pattern Analysis and Machine Intelligence Feb 1992 18,308
3 Bayesian Analysis of Radiocarbon Dates Christopher Bronk Ramsey · Radiocarbon Open access 2009 8,832
4 Active Shape Models-Their Training and Application Tim F. Cootes, Chris Taylor, David H. Cooper et al. · Computer Vision and Image Understanding Open access 1995 7,230
5 Shape matching and object recognition using shape contexts Serge Belongie, Jitendra Malik, Jan Puzicha · IEEE Transactions on Pattern Analysis and Machine Intelligence Apr 2002 6,358
All 99 most cited papers, with filters and sorting

Where is Image Processing and 3D Reconstruction research done?

The largest centres of Image Processing and 3D Reconstruction research in 2022-now are Beijing (China), Shanghai (China), Wuhan (China) and Xi'an (China).

Largest cities, 2022-now

  1. 1 BeijingChina 443 works
  2. 2 ShanghaiChina 139 works
  3. 3 WuhanChina 116 works
  4. 4 Xi'anChina 115 works
  5. 5 NanjingChina 90 works
  6. 6 MoscowRussia 82 works
  7. 7 ChengduChina 71 works
  8. 8 GuangzhouChina 67 works
  9. 9 HangzhouChina 60 works
  10. 10 TokyoJapan 59 works
See Image Processing and 3D Reconstruction on the map

Where is the best place to study Image Processing and 3D Reconstruction?

Among universities, judged by research, Tsinghua University, Shanghai Jiao Tong University and Zhejiang 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 25.64%fractional works in this field (log) →share of work in the world top 10% →Zhejiang UniversityTsinghua UniversityShanghai Jiao Tong U…Peking 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
1Tsinghua UniversityChina 69.526.0%2.3×29 +154.8%
2Shanghai Jiao Tong UniversityChina 66.322.5%1.9×30 +133.3%
3Zhejiang UniversityChina 61.126.4%1.5×22 +180.5%
4Peking UniversityChina 61.021.9%1.7×19 +76.2%
5University of Hong KongChina 61.023.9%2.5×13 +405.9%
6Carnegie Mellon UniversityUnited States 60.725.2%4.4×10 +109.0%
7Stanford UniversityUnited States 60.033.1%1.2×10 +55.1%
8Technical University of MunichGermany 59.826.2%2.4×12 +111.6%
9Hong Kong Polytechnic UniversityChina 58.732.5%2.2×11 +243.6%
10University of Science and Technology of ChinaChina 57.818.7%3.0×20 +130.4%

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 Image Processing and 3D Reconstruction, country by country

Is Image Processing and 3D Reconstruction research growing?

Output in 2022-2025 was 50% higher than in 2018-2021, peaking in 2024. The fastest-growing topics are Image Processing and 3D Reconstruction.

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 Image Processing and 3D Reconstruction as a percentage of every work published that year, 0.039% in 2024.

still counting0.020%0.040%Image Processing and 3D Reconstruction0.033% in 202519801990200020102020

Fractional works of Image Processing and 3D Reconstruction 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%Image Processing and 3D Reconstruction9.9% 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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