Connor Z. Lin
- Computer Vision and Pattern Recognition top 2%
- Computer Graphics and Computer-Aided Design top 1%
- Computational Mechanics top 5%
- Control and Systems Engineering
- Artificial Intelligence
- Co-authors
- Gordon WetzsteinEric R. ChanSameh KhamisTero KarrasBoxiao PanKoki NaganoMatthew A. ChanShalini De Mello
- Topics
- 3D Shape Modeling and Analysis (3 papers)Computer Graphics and Visualization Techniques (3 papers)Advanced Vision and Imaging (3 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionComputational Mechanics
- Journals
- ACM Transactions on GraphicsACM Transactions on Applied Perception2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United States
In The Last Decade
Connor Z. Lin
4 papers receiving 703 citations
Hit Papers
Peers
Comparison fields: 5 of 61
- Computer Vision and Pattern Recognition 576
- Computer Graphics and Computer-Aided Design 341
- Computational Mechanics 322
- Control and Systems Engineering 49
- Artificial Intelligence 45
Countries citing papers authored by Connor Z. Lin
This map shows the geographic impact of Connor Z. Lin'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 Connor Z. Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Connor Z. Lin more than expected).
Fields of papers citing papers by Connor Z. Lin
This network shows the impact of papers produced by Connor Z. Lin. 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 Connor Z. Lin. The network helps show where Connor Z. Lin may publish in the future.
Co-authorship network of co-authors of Connor Z. Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Connor Z. Lin. A scholar is included among the top collaborators of Connor Z. Lin 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 Connor Z. Lin. Connor Z. Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | Efficient Geometry-aware 3D Generative Adversarial Networksbreakdown → | 600 |
| 3 | 111 | |
| 4 | 3 |
About Connor Z. Lin
Connor Z. Lin is a scholar working on Computer Graphics and Computer-Aided Design, Sensory Systems and Computer Vision and Pattern Recognition, having authored 4 papers that have together received 716 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (3 papers), Computer Graphics and Visualization Techniques (3 papers) and Advanced Vision and Imaging (3 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (341 citations), Computer Vision and Pattern Recognition (576 citations) and Computational Mechanics (322 citations). Connor Z. Lin has collaborated with scholars based in United States. Frequent co-authors include Gordon Wetzstein, Eric R. Chan, Sameh Khamis, Tero Karras, Boxiao Pan, Koki Nagano, Matthew A. Chan, Shalini De Mello, Orazio Gallo and Leonidas Guibas. Their work appears in journals such as ACM Transactions on Graphics, ACM Transactions on Applied Perception and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.