Erika Lu

575 citations
9 papers · 268 · h-index 6

Impact in

Papers in

Erika Lu

8 papers receiving 260 citations

Peers

Erika Lu
Comparison fields: 5 of 35
  • Computer Vision and Pattern Recognition 239
  • Computer Graphics and Computer-Aided Design 22
  • Artificial Intelligence 59
  • Human-Computer Interaction 7
  • Media Technology 10
Replace Toshikazu Wada with:
Toshikazu Wada Japan
Marcelo Bernardes Vieira Brazil
Yiwei Ma China
Haozhi Huang China
Artsiom Sanakoyeu Germany
Sungheon Park South Korea
Dong Huk Park United States
Fuwen Tan United States
Vighnesh Birodkar United States
Sezer Karaoğlu Netherlands
Erika Lu relative to Toshikazu Wada Japan Toshikazu Wada's profile →
Citations per field
00.5×11.7×
Toshikazu Wada · 1×
Citations per year

Countries citing papers authored by Erika Lu

Since Specialization
Citations

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

Fields of papers citing papers by Erika Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 202094
2 202176
3
Learning to See Physics via Visual De-animation
201742
4 202029
5 202120
6 20235
7 20251
8 20231
9 20240

About Erika Lu

Erika Lu is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Computer Graphics and Computer-Aided Design, Infectious Diseases and Organic Chemistry, having authored 9 papers that have together received 268 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (6 papers), Video Surveillance and Tracking Methods (3 papers), Human Pose and Action Recognition (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Advanced Image Processing Techniques (2 papers), Visual Attention and Saliency Detection (2 papers), Image Enhancement Techniques (2 papers) and Computer Graphics and Visualization Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (239 citations), Computer Graphics and Computer-Aided Design (22 citations), Artificial Intelligence (59 citations), Human-Computer Interaction (7 citations) and Media Technology (10 citations). Erika Lu has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Weidi Xie, Zihang Lai, Andrew Zisserman, Bill Freeman, Jiajun Wu, Pushmeet Kohli, Josh Tenenbaum, Michael Rubinstein, William T. Freeman and Tali Dekel. Their work appears in journals such as ACM Transactions on Graphics, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and DSpace@MIT (Massachusetts Institute of Technology).

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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