Daniel Scharstein
Impact in
- Computer Vision and Pattern Recognition top 0.02%
- Advanced Vision and Imaging
- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Advanced Image and Video Retrieval Techniques
- Optical measurement and interference techniques
- Media Technology top 0.05%
- Image Processing Techniques and Applications
Papers in
-
- Advanced Vision and Imaging 35
- Advanced Image and Video Retrieval Techniques 17
- Advanced Image Processing Techniques 16
- Image Enhancement Techniques 14
- Optical measurement and interference techniques 4
- Robotic Path Planning Algorithms 4
-
- Robotics and Sensor-Based Localization 12
- Co-authors
- Rick Szeliski (3 shared papers)Richard Szeliski (14 shared papers)Heiko Hirschmüller (5 shared papers)Ramin Zabih (3 shared papers)Brian Curless (1 shared paper)James Diebel (1 shared paper)Steven M. Seitz (1 shared paper)Simon Baker (2 shared papers)
- Journals
- International Journal of Computer Vision (5 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (4 papers)ACM Transactions on Graphics (3 papers)Image and Vision Computing (2 papers)The International Journal of Robotics Research (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Daniel Scharstein
47 papers receiving 15.8k citations
Daniel Scharstein's Hit Papers
Peers
Comparison fields: 5 of 146
- Computer Vision and Pattern Recognition 14.9k
- Media Technology 3.8k
- Computer Graphics and Computer-Aided Design 1.3k
- Geology 1.2k
- Aerospace Engineering 3.3k
Countries citing papers authored by Daniel Scharstein
This map shows the geographic impact of Daniel Scharstein'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 Scharstein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Scharstein more than expected).
Fields of papers citing papers by Daniel Scharstein
This network shows the impact of papers produced by Daniel Scharstein. 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 Scharstein. The network helps show where Daniel Scharstein may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Scharstein, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms Hit paper breakdown → | 2002 | 5205 |
| 2 | A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms Hit paper breakdown → | 2006 | 1863 |
| 3 | A Database and Evaluation Methodology for Optical Flow Hit paper breakdown → | 2010 | 1597 |
| 4 | High-accuracy stereo depth maps using structured light Hit paper breakdown → | 2003 | 1179 |
| 5 | High-Resolution Stereo Datasets with Subpixel-Accurate Ground Truth Hit paper breakdown → | 2014 | 907 |
| 6 | Evaluation of Cost Functions for Stereo Matching Hit paper breakdown → | 2007 | 864 |
| 7 | A taxonomy and evaluation of dense two-frame stereo correspondence algorithms Hit paper breakdown → | 2002 | 780 |
| 8 | A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors Hit paper breakdown → | 2008 | 740 |
| 9 | Learning Conditional Random Fields for Stereo Hit paper breakdown → | 2007 | 675 |
| 10 | Evaluation of Stereo Matching Costs on Images with Radiometric Differences Hit paper breakdown → | 2008 | 583 |
| 11 | A Database and Evaluation Methodology for Optical Flow Hit paper breakdown → | 2007 | 470 |
| 12 | 2006 | 317 | |
| 13 | 1998 | 196 | |
| 14 | 2011 | 115 | |
| 15 | 2012 | 93 | |
| 16 | 2014 | 90 | |
| 17 | 1999 | 88 | |
| 18 | 2022 | 79 | |
| 19 | 1996 | 76 | |
| 20 | 2009 | 72 |
About Daniel Scharstein
Daniel Scharstein is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Media Technology, Computer Graphics and Computer-Aided Design and Computer Networks and Communications, having authored 47 papers that have together received 16.6k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (35 papers), Advanced Image and Video Retrieval Techniques (17 papers), Advanced Image Processing Techniques (16 papers), Image Enhancement Techniques (14 papers), Robotics and Sensor-Based Localization (12 papers), Image Processing Techniques and Applications (5 papers), Optical measurement and interference techniques (4 papers) and Robotic Path Planning Algorithms (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (14.9k citations), Media Technology (3.8k citations), Computer Graphics and Computer-Aided Design (1.3k citations), Geology (1.2k citations) and Aerospace Engineering (3.3k citations). Daniel Scharstein has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Rick Szeliski, Richard Szeliski, Heiko Hirschmüller, Ramin Zabih, Brian Curless, James Diebel, Steven M. Seitz, Simon Baker, John Lewis and Michael J. Black. Their work appears in journals such as International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics, Image and Vision Computing and The International Journal of Robotics Research.
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.