Iro Laina

2.3k citations
13 papers · 505 · 2 hit papers · h-index 7

Impact in

Papers in

Iro Laina

10 papers receiving 490 citations

Iro Laina's Hit Papers

Training-Free Layout Control with Cross-Attention Guidance 2024 · 55 citations
550+1+2Years since publication255075

Peers

Iro Laina
Comparison fields: 5 of 62
  • Computer Graphics and Computer-Aided Design 108
  • Computer Vision and Pattern Recognition 392
  • Artificial Intelligence 148
  • Computational Mechanics 89
  • Geology 21
Replace Jiemin Fang with:
Jiemin Fang China
Guangcong Wang China
Yingchen Yu Singapore
Ignas Budvytis United Kingdom
Tianfan Xue Hong Kong
Andreas Lehrmann Germany
Yunqi Lei China
Shuaifeng Zhi China
Vincent Casser Germany
Amir Hertz Israel
Iro Laina relative to Jiemin Fang China Jiemin Fang's profile →
Citations per field
00.5×
Jiemin Fang · 1×
Citations per year

Countries citing papers authored by Iro Laina

Since Specialization
Citations

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

Fields of papers citing papers by Iro Laina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Iro Laina, 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 Iro Laina Line = papers co-authored together Iro Laina links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1
RealFusion 360° Reconstruction of Any Object from a Single Image
Hit paper breakdown →
202390
2 202287
3 201781
4 202275
5 202072
6
Training-Free Layout Control with Cross-Attention Guidance
Hit paper breakdown →
202455
7 201935
8 20236
9 20243
10 20251
11 20240
12 20210
13 20250

About Iro Laina

Iro Laina is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Media Technology, having authored 13 papers that have together received 505 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (3 papers), Computer Graphics and Visualization Techniques (3 papers), Multimodal Machine Learning Applications (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Advanced Vision and Imaging (2 papers), 3D Surveying and Cultural Heritage (2 papers), Advanced Neural Network Applications (2 papers) and Image Processing Techniques and Applications (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (108 citations), Computer Vision and Pattern Recognition (392 citations), Artificial Intelligence (148 citations), Computational Mechanics (89 citations) and Geology (21 citations). Iro Laina has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Andrea Vedaldi, Christian Rupprecht, Luke Melas-Kyriazi, Federico Tombari, Nassir Navab, Gregory D. Hager, Diane Larlus, Minghao Chen, Maximilian Baust and Robert DiPietro. Their work appears in journals such as Pattern Recognition Letters, International Journal of Computer Vision, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and PubMed.

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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