Liuhui Wang

19 papers receiving 277 citations

Liuhui Wang's Hit Papers

Learning 3D Representations from 2D Pre-Trained Models via Image-to-Point Masked Autoencoders 2023 · 83 citations
830+1+2Years since publication255075

Peers

Liuhui Wang
Comparison fields: 5 of 83
  • Geology 61
  • Computer Graphics and Computer-Aided Design 29
  • Computational Mechanics 89
  • Computer Vision and Pattern Recognition 81
  • Environmental Engineering 38
Replace Cho-Ying Wu with:
Cho-Ying Wu United States
Mu Cai United States
Tanmay Gupta India
Amin Zheng Hong Kong
Gusi Te China
Sudhakar Kumawat India
Zizheng Yan China
Haowen Deng China
Khoi Nguyen Vietnam
Heyu Zhou China
Liuhui Wang relative to Cho-Ying Wu United States Cho-Ying Wu's profile →
Citations per field
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Cho-Ying Wu · 1×
Citations per year

Countries citing papers authored by Liuhui Wang

Since Specialization
Citations

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

Fields of papers citing papers by Liuhui Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Learning 3D Representations from 2D Pre-Trained Models via Image-to-Point Masked Autoencoders
Hit paper breakdown →
202383
2 202360
3 202215
4 202014
5 202311
6 202111
7 202311
8 201910
9 202310
10 20219
11 20188
12 20217
13 20206
14 20236
15 20145
16 20255
17 20233
18 20203
19 20192
20 20250

About Liuhui Wang

Liuhui Wang is a scholar working on Dermatology, Information Systems, Computational Mechanics, Artificial Intelligence and Automotive Engineering, having authored 22 papers that have together received 279 indexed citations. Recurring topics across this work include Dermatology and Skin Diseases (5 papers), 3D Shape Modeling and Analysis (3 papers), Autonomous Vehicle Technology and Safety (2 papers), 3D Surveying and Cultural Heritage (2 papers), Recommender Systems and Techniques (2 papers), Advanced Bandit Algorithms Research (2 papers), Computer Graphics and Visualization Techniques (2 papers) and Folate and B Vitamins Research (1 paper). The work is most often cited by research in Geology (61 citations), Computer Graphics and Computer-Aided Design (29 citations), Computational Mechanics (89 citations), Computer Vision and Pattern Recognition (81 citations) and Environmental Engineering (38 citations). Liuhui Wang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Renrui Zhang, Peng Gao, Hongsheng Li, Yu Qiao, Jianbo Shi, Yali Wang, Weili Yan, Xinyu Lin, Tat‐Seng Chua and Fuli Feng. Their work appears in journals such as Pediatric Allergy and Immunology, Pediatric Research, The Journal of Dermatology, Frontiers in Public Health and Dermatologic Therapy.

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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