Yifeng Shi

1.0k citations
18 papers · 575 indexed · 2 hit papers · h-index 10
Topics
Advanced Neural Network Applications (8 papers)Video Surveillance and Tracking Methods (5 papers)Autonomous Vehicle Technology and Safety (3 papers)

In The Last Decade

Yifeng Shi

17 papers receiving 564 citations

Hit Papers

DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructur...20222026202320242022202550100150200250

Peers

Yifeng Shi
Comparison fields: 5 of 55
  • Computer Vision and Pattern Recognition 388
  • Automotive Engineering 177
  • Aerospace Engineering 127
  • Artificial Intelligence 78
  • Environmental Engineering 75
Replace Luís Garrote with:
Luís Garrote Portugal
Jirui Yuan China
Qichuan Geng China
Mauro Bellone Estonia
Takashi Naito Japan
Haibao Yu China
Eduardo Arnold United Kingdom
Thierry Château France
Zhiyu Xiang China
Yifeng Shi relative to Luís Garrote Portugal Luís Garrote's profile →
Citations per field
00.5×4.7×
Luís Garrote · 1×
Citations per year

Countries citing papers authored by Yifeng Shi

Since Specialization
Citations

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

Fields of papers citing papers by Yifeng Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yifeng Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Yifeng Shi. A scholar is included among the top collaborators of Yifeng Shi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yifeng Shi. Yifeng Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1
RT-DETRv3: Real-Time End-to-End Object Detection with Hierarchical Dense Positive Supervisionbreakdown →
19
2 1
3 9
4 2
5 81
6 18
7
DAIR-V2X: A Large-Scale Dataset for Vehicle-Infrastructure Cooperative 3D Object Detectionbreakdown →
277
8 1
9 0
10 77
11 17
12 27
13 19
14 18
15 3
16 4
17 1
18 1

About Yifeng Shi

Yifeng Shi is a scholar working on Computer Vision and Pattern Recognition, Energy Engineering and Power Technology and Automotive Engineering, having authored 18 papers that have together received 575 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Video Surveillance and Tracking Methods (5 papers) and Autonomous Vehicle Technology and Safety (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (388 citations), Automotive Engineering (177 citations) and Instrumentation (35 citations). Yifeng Shi has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Hanyu Li, Zaiqing Nie, Haibao Yu, Jirui Yuan, Zhenglong Guo, Xing Hu, Yizhen Luo, Zebang Yang, Xiao Tan and Errui Ding. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, National Science Review and Mathematical Problems in 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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