Xin Ning

6.6k citations
161 papers · 4.4k · 3 hit papers · h-index 39

Impact in

Papers in

Xin Ning

149 papers receiving 4.3k citations

Xin Ning's Hit Papers

Cross-modal knowledge transfer for 3D point clouds via graph offset prediction 2025 · 32 citations
320+1+2Years since publication255075100

Peers

Xin Ning
Comparison fields: 5 of 160
  • Computer Vision and Pattern Recognition 2.1k
  • Media Technology 381
  • Artificial Intelligence 1.2k
  • Computer Graphics and Computer-Aided Design 121
  • Business and International Management 62
Replace Yujie Li with:
Yujie Li China
Weijun Li China
Sergiu Nedevschi Romania
Jiachen Yang China
Xiao Bai China
Seiichi Serikawa Japan
C. Krishna Mohan India
Xiaonan Luo China
Sicheng Zhao China
Jun Guo China
Xin Ning relative to Yujie Li China Yujie Li's profile →
Citations per field
00.5×2.6×
Yujie Li · 1×
Citations per year

Countries citing papers authored by Xin Ning

Since Specialization
Citations

This map shows the geographic impact of Xin Ning'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 Xin Ning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xin Ning more than expected).

Fields of papers citing papers by Xin Ning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xin Ning. 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 Xin Ning. The network helps show where Xin Ning may publish in the future.

Co-authors

The 25 scholars most cited alongside Xin Ning, 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 Xin Ning Line = papers co-authored together Xin Ning links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 161 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020205
2 2021186
3 2021154
4 2021153
5 2021144
6 2020129
7
Deep learning-based 3D point cloud classification: A systematic survey and outlook
Hit paper breakdown →
2023114
8 2020106
9 2022102
10 202298
11 202397
12 202295
13 202181
14 201877
15 202074
16 202172
17 202272
18 202370
19 202169
20 201967

About Xin Ning

Xin Ning is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Computational Mechanics and Media Technology, having authored 161 papers that have together received 4.4k indexed citations. Recurring topics across this work include Face recognition and analysis (34 papers), Face and Expression Recognition (23 papers), Video Surveillance and Tracking Methods (19 papers), Human Pose and Action Recognition (16 papers), Generative Adversarial Networks and Image Synthesis (16 papers), Biometric Identification and Security (15 papers), 3D Shape Modeling and Analysis (13 papers) and Advanced Neural Network Applications (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.1k citations), Media Technology (381 citations), Artificial Intelligence (1.2k citations), Computer Graphics and Computer-Aided Design (121 citations) and Business and International Management (62 citations). Xin Ning has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Weijun Li, Xiao Bai, Weiwei Cai, Liping Zhang, Prayag Tiwari, Changshuo Wang, Linjun Sun, Shengwei Tian, Lina Yu and Huang Zhang. Their work appears in journals such as Information Fusion, Pattern Recognition, Displays, Neural Networks and Expert Systems with Applications.

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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