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Researcher · Cornell University · United States

Noah Snavely

Noah Snavely publishes mostly in Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Aerospace Engineering, on topics such as Advanced Vision and Imaging, Advanced Image and Video Retrieval Techniques and Computer Graphics and Visualization Techniques.

ORCID 0000-0002-6921-6833 OpenAlex
World rank
#10,266
of 7,710,434 ranked researchers
Rank in United States
#3,534
of 1,627,098
Works
252
Citations
29k
Citations per work
115.0
h-index
64
i10-index 133Top 0.5% in Computer Vision and Pattern Recognition
Noah Snavely

What does Noah Snavely research?

Noah Snavely's work is mostly in Computer Science (69%), Engineering (14%), Earth and Planetary Sciences (2%).

Physical Sciences: 220 works · 87.2% of their workComputer Science: 174 works · 69.2% of their workComputer Vision and Pattern Recognition: 150 works · 59.6% of their workComputer Graphics and Computer-Aided Design: 24 works · 9.6% of their workEngineering: 35 works · 13.8% of their workAerospace Engineering: 22 works · 8.8% of their workComputational Mechanics: 13 works · 5.0% of their workEarth and Planetary Sciences: 6 works · 2.4% of their workGeology: 6 works · 2.4% of their workEnvironmental Science: 5 works · 1.8% of their workEnvironmental Engineering: 5 works · 1.8% of their workEverything else: 32 works · 12.8% of their workTHEIR WORKNoah Snavely252works
Physical Sciences87%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science17469.2%
    2. Engineering3513.8%
    3. Earth and Planetary Sciences62.4%
    4. Environmental Science51.8%
  2. Everything else3212.8%
  1. 1Computer Vision and Pattern Recognition60% of their works
  2. 2Computer Graphics and Computer-Aided Design10% of their works
  3. 3Aerospace Engineering9% of their works
  4. 4Computational Mechanics5% of their works
  5. 5Geology2% of their works
  6. 6Environmental Engineering2% of their works

Research topics

Which keywords describe Noah Snavely's research?

The keywords of their largest research topics: Deep Learning, Convolutional Networks, Unsupervised Learning, Depth Estimation, Stereo Vision, Feature Matching, Local Descriptors and Computer Graphics.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 21 words, with their numbers
  1. Deep Learning1965 topics
  2. Convolutional Networks1922 topics
  3. Unsupervised Learning1902 topics
  4. Depth Estimation1581 topic
  5. Stereo Vision1581 topic
  6. Feature Matching711 topic
  7. Local Descriptors711 topic
  8. Computer Graphics701 topic
  9. Visualization701 topic
  10. Generative Adversarial Networks662 topics
  11. Neural Networks662 topics
  12. 3D Mapping631 topic
  13. SLAM631 topic
  14. Image341 topic
  15. Super-Resolution341 topic
  16. Image Inpainting321 topic
  17. Image Synthesis321 topic
  18. 3D Reconstruction311 topic
  19. Point Clouds311 topic
  20. Contrast Enhancement281 topic
  21. Dehazing281 topic

Where does Noah Snavely work?

Noah Snavely's main affiliation in the publication record is Cornell University, United States.

How many publications and citations does Noah Snavely have?

OpenAlex counts 252 works and 28,976 citations for Noah Snavely, an h-index of 64, ranking #10,266 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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