Xingyu Liu

4.8k citations
15 papers · 1.9k indexed · 2 hit papers · h-index 7

Impact in

Papers in

Xingyu Liu

12 papers receiving 1.9k citations

Hit Papers

FlowNet3D: Learning Scene Flow in 3D Point Clouds 2019 · 307 citations
30720162026201920224008001.2k

Peers

Xingyu Liu
Comparison fields: 5 of 86
  • Computer Vision and Pattern Recognition 1.3k
  • Computational Mathematics 31
  • Hardware and Architecture 234
  • Computer Graphics and Computer-Aided Design 78
  • Artificial Intelligence 672
Replace Huizi Mao with:
Huizi Mao United States
Jonathan Ragan‐Kelley United States
Ninghui Sun China
Brody Huval United States
Baoyuan Wu China
Yingyan Lin United States
Jaewoong Sim United States
Marshall F. Tappen United States
Jincheng Yu China
P. J. Narayanan India
Xingyu Liu relative to Huizi Mao United States Huizi Mao's profile →
Citations per field
00.5×3.7×
Huizi Mao · 1×
Citations per year

Countries citing papers authored by Xingyu Liu

Since Specialization
Citations

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

Fields of papers citing papers by Xingyu Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 20250
2 20243
3 20240
4 20236
5 20231
6 20218
7 20216
8 20210
9 202042
10 2019142
11
FlowNet3D: Learning Scene Flow in 3D Point Clouds
Hit paper breakdown →
2019307
12 20181
13 201712
14 2017129
15
EIE
Hit paper breakdown →
20161277

About Xingyu Liu

Xingyu Liu is a scholar working on Structural Biology, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Human-Computer Interaction and Biophysics, having authored 15 papers that have together received 1.9k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (3 papers), Advanced Neural Network Applications (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Advanced Text Analysis Techniques (2 papers), Computer Graphics and Visualization Techniques (2 papers), Advanced Vision and Imaging (2 papers), Advanced Image Processing Techniques (2 papers) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Computational Mathematics (31 citations), Hardware and Architecture (234 citations), Computer Graphics and Computer-Aided Design (78 citations) and Artificial Intelligence (672 citations). Xingyu Liu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include William J. Dally, Huizi Mao, Song Han, Mark Horowitz, Jing Pu, Ardavan Pedram, Leonidas Guibas, Charles R. Qi, Jeannette Bohg and Mengyuan Yan. Their work appears in journals such as Colloids and Surfaces A Physicochemical and Engineering Aspects, Infection and Drug Resistance, Drones, Lecture notes in computer science and Computational Biology and Chemistry.

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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