Angela Dai

43 papers receiving 5.1k citations

Hit Papers

ScanNet: Richly-Annotated 3D Reconstructions of Indoor Sc...2017202620202023201720172017201950010001.5k2.0k

Peers

Angela Dai
Comparison fields: 5 of 90
  • Computer Vision and Pattern Recognition 3.7k
  • Computational Mechanics 1.9k
  • Aerospace Engineering 1.9k
  • Geology 1.8k
  • Computer Graphics and Computer-Aided Design 904
Replace Manolis Savva with:
Manolis Savva United States
Maciej Halber United States
Qian-Yi Zhou United States
Jaesik Park South Korea
Chiew‐Lan Tai Hong Kong
Daniel Maturana United States
Richard A. Newcombe United Kingdom
Gim Hee Lee Singapore
Linguang Zhang United States
Shaoshuai Shi Hong Kong
Angela Dai relative to Manolis Savva United States Manolis Savva's profile →
Citations per field
00.5×1.6×
Manolis Savva · 1×
Citations per year

Countries citing papers authored by Angela Dai

Since Specialization
Citations

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

Fields of papers citing papers by Angela Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Angela Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Angela Dai. A scholar is included among the top collaborators of Angela Dai 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 Angela Dai. Angela Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 0
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5 7
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7 19
8 0
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10 17
11 7
12 5
13 1
14 18
15 31
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17 2
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3D-SIC: 3D Semantic Instance Completion for RGB-D Scans
3
19 54
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ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenesbreakdown →
2255

About Angela Dai

Angela Dai is a scholar working on Computer Graphics and Computer-Aided Design, Geology and Computer Vision and Pattern Recognition, having authored 48 papers that have together received 5.2k indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (24 papers), Advanced Vision and Imaging (17 papers) and Computer Graphics and Visualization Techniques (15 papers). The work is most often cited by research in Geology (1.8k citations), Computer Graphics and Computer-Aided Design (904 citations) and Computer Vision and Pattern Recognition (3.7k citations). Angela Dai has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Matthias Nießner, Manolis Savva, Anne Lynn S. Chang, Thomas Funkhouser, Maciej Halber, Matthias NieBner, Christian Theobalt, Michael Zollhöfer, Shahram Izadi and Shuran Song. Their work appears in journals such as ACM Transactions on Graphics, Journal of Mechanical Design and Computer Graphics Forum.

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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