Jun Gao

4.2k citations
122 papers · 2.3k indexed · 1 hit paper · h-index 23

Jun Gao

111 papers receiving 2.2k citations

Hit Papers

Magic3D: High-Resolution Text-to-3D Content Creation3872023202620242025100200300

Peers

Jun Gao
Comparison fields: 5 of 159
  • Computer Graphics and Computer-Aided Design 283
  • Computer Vision and Pattern Recognition 892
  • Nutrition and Dietetics 432
  • Nephrology 166
  • Food Science 393
Replace John A. Hossack with:
John A. Hossack United States
Yipeng Zhang China
Shigang Li China
Xiaoming Wei China
Changming Sun Australia
Chenghua Wang China
Peng Deng China
Kai Huang China
Siyuan Li China
Jun Gao relative to John A. Hossack United States John A. Hossack's profile →
Citations per field
00.5×10×20×30×35.4×
John A. Hossack · 1×
Citations per year

Countries citing papers authored by Jun Gao

Since Specialization
Citations

This map shows the geographic impact of Jun Gao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jun Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Gao more than expected).

Fields of papers citing papers by Jun Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Gao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Gao. The network helps show where Jun Gao may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jun Gao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Gao Line = papers co-authored together Jun Gao links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20253
4 202422
5 20244
6 20246
7 20234
8 20231
9 20234
10 20221
11 20218
12 202114
13 202034
14
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer
201933
15 20166
16 20161
17
Saliency detection with a deeper investigation of light field
201533
18
Modeling of Skylight Polarization Pattern Based on Electric Vector
20102
19 20107
20
A Novel Method for Scene Categorization with Constraint Mechanism Based on Gaussian Statistical Model
20092

About Jun Gao

Jun Gao is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Acoustics and Ultrasonics, having authored 122 papers that have together received 2.3k indexed citations. Recurring topics across this work include Face and Expression Recognition (11 papers), Food composition and properties (10 papers), Advanced Image and Video Retrieval Techniques (10 papers), Proteins in Food Systems (9 papers), Advanced Vision and Imaging (9 papers), Optical measurement and interference techniques (9 papers), Video Surveillance and Tracking Methods (8 papers) and Image Retrieval and Classification Techniques (8 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (283 citations), Computer Vision and Pattern Recognition (892 citations) and Nutrition and Dietetics (432 citations). Jun Gao has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Thava Vasanthan, Sanja Fidler, R. Hoover, Huan Ling, Demetrios J. Kutsogiannis, Daniel Stollery, R. T. Noel Gibney, Tsung-Yi Lin, Luming Tang and Wenzheng Chen. Their work appears in journals such as Food Hydrocolloids, Pattern Recognition, IEEE Transactions on Instrumentation and Measurement, Applied Optics and Optical Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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