Daniel Rho
Impact in
-
- Computer Graphics and Visualization Techniques
- Signal Processing top 5%
- Video Coding and Compression Technologies
Papers in
-
- Video Coding and Compression Technologies 2
- Speech and Audio Processing 1
-
- 3D Shape Modeling and Analysis 5
- Co-authors
- Jong Hwan Ko (8 shared papers)Eun Byung Park (6 shared papers)Joo Chan Lee (4 shared papers)Jin‐Hyeok Park (1 shared paper)Usman Ali (1 shared paper)
- Journals
- Lecture notes in computer science (2 papers)neural information processing systems (1 paper)ACM International Conference on Multimedia (ACM MM) (2 papers)IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (2 papers)Interspeech (USB) (1 paper)
- Partner nations
- South Korea
In The Last Decade
Daniel Rho
8 papers receiving 254 citations
Daniel Rho's Hit Papers
Peers
Comparison fields: 5 of 15
- Computer Graphics and Computer-Aided Design 68
- Signal Processing 74
- Computational Mechanics 173
- Computer Vision and Pattern Recognition 45
- Hardware and Architecture 6
Countries citing papers authored by Daniel Rho
This map shows the geographic impact of Daniel Rho'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 Daniel Rho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Rho more than expected).
Fields of papers citing papers by Daniel Rho
This network shows the impact of papers produced by Daniel Rho. 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 Daniel Rho. The network helps show where Daniel Rho may publish in the future.
Co-authors
The 5 scholars most cited alongside Daniel Rho, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Compact 3D Gaussian Representation for Radiance Field Hit paper breakdown → | 2024 | 154 |
| 2 | 2023 | 42 | |
| 3 | 2023 | 29 | |
| 4 | 2023 | 13 | |
| 5 | 2022 | 12 | |
| 6 | 2022 | 5 | |
| 7 | 2024 | 4 | |
| 8 | 2023 | 2 |
About Daniel Rho
Daniel Rho is a scholar working on Signal Processing, Computational Mechanics, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 261 indexed citations. Recurring topics across this work include 3D Shape Modeling and Analysis (5 papers), Video Coding and Compression Technologies (2 papers), Computer Graphics and Visualization Techniques (2 papers), Speech and Audio Processing (1 paper), Speech Recognition and Synthesis (1 paper), Generative Adversarial Networks and Image Synthesis (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (68 citations), Signal Processing (74 citations), Computational Mechanics (173 citations), Computer Vision and Pattern Recognition (45 citations) and Hardware and Architecture (6 citations). Daniel Rho has collaborated with scholars based in South Korea. Frequent co-authors include Jong Hwan Ko, Eun Byung Park, Joo Chan Lee, Jin‐Hyeok Park and Usman Ali. Their work appears in journals such as Lecture notes in computer science, neural information processing systems, ACM International Conference on Multimedia (ACM MM), IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings and Interspeech (USB).
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.