C. Schmid
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Media Technology top 0.05%
- Remote-Sensing Image Classification
Papers in
-
- Advanced Image and Video Retrieval Techniques 38
- Image Retrieval and Classification Techniques 29
- Advanced Vision and Imaging 10
- Video Analysis and Summarization 8
- Medical Image Segmentation Techniques 6
- Multimodal Machine Learning Applications 5
-
- Robotics and Sensor-Based Localization 12
- Co-authors
- Krystian Mikolajczyk (8 shared papers)Svetlana Lazebnik (11 shared papers)Jean Ponce (9 shared papers)Roger Mohr (2 shared papers)Marcin Marszałek (4 shared papers)Andrew Zisserman (4 shared papers)Jianguo Zhang (3 shared papers)M. Marszałek (1 shared paper)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (9 papers)International Journal of Computer Vision (2 papers)Computational Statistics & Data Analysis (1 paper)IEEE Transactions on Image Processing (1 paper)Lecture notes in computer science (3 papers)
- Partner nations
- FranceUnited StatesUnited Kingdom
In The Last Decade
C. Schmid
49 papers receiving 24.5k citations
C. Schmid's Hit Papers
Peers
Comparison fields: 5 of 176
- Computer Vision and Pattern Recognition 23.8k
- Media Technology 3.8k
- Aerospace Engineering 7.2k
- Human-Computer Interaction 715
- Artificial Intelligence 3.9k
Countries citing papers authored by C. Schmid
This map shows the geographic impact of C. Schmid'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 C. Schmid with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Schmid more than expected).
Fields of papers citing papers by C. Schmid
This network shows the impact of papers produced by C. Schmid. 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 C. Schmid. The network helps show where C. Schmid may publish in the future.
Co-authors
The 25 scholars most cited alongside C. Schmid, 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 50 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories Hit paper breakdown → | 2006 | 6184 |
| 2 | A performance evaluation of local descriptors Hit paper breakdown → | 2005 | 5187 |
| 3 | A Comparison of Affine Region Detectors Hit paper breakdown → | 2005 | 2294 |
| 4 | Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study Hit paper breakdown → | 2006 | 1547 |
| 5 | A Spatio-Temporal Descriptor Based on 3D-Gradients Hit paper breakdown → | 2008 | 1464 |
| 6 | Local grayvalue invariants for image retrieval Hit paper breakdown → | 1997 | 1144 |
| 7 | Aggregating Local Image Descriptors into Compact Codes Hit paper breakdown → | 2011 | 1124 |
| 8 | A sparse texture representation using local affine regions Hit paper breakdown → | 2005 | 908 |
| 9 | Indexing based on scale invariant interest points Hit paper breakdown → | 2002 | 819 |
| 10 | A performance evaluation of local descriptors Hit paper breakdown → | 2003 | 701 |
| 11 | Learning Color Names for Real-World Applications Hit paper breakdown → | 2009 | 546 |
| 12 | Groups of Adjacent Contour Segments for Object Detection Hit paper breakdown → | 2007 | 448 |
| 13 | Learning object class detectors from weakly annotated video Hit paper breakdown → | 2012 | 300 |
| 14 | 2005 | 258 | |
| 15 | 2007 | 256 | |
| 16 | 2002 | 198 | |
| 17 | 2012 | 186 | |
| 18 | 2002 | 179 | |
| 19 | 2004 | 172 | |
| 20 | 2008 | 168 |
About C. Schmid
C. Schmid is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Media Technology, Artificial Intelligence and Control and Systems Engineering, having authored 50 papers that have together received 26.1k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (38 papers), Image Retrieval and Classification Techniques (29 papers), Robotics and Sensor-Based Localization (12 papers), Advanced Vision and Imaging (10 papers), Remote-Sensing Image Classification (8 papers), Video Analysis and Summarization (8 papers), Medical Image Segmentation Techniques (6 papers) and Multimodal Machine Learning Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (23.8k citations), Media Technology (3.8k citations), Aerospace Engineering (7.2k citations), Human-Computer Interaction (715 citations) and Artificial Intelligence (3.9k citations). C. Schmid has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Krystian Mikolajczyk, Svetlana Lazebnik, Jean Ponce, Roger Mohr, Marcin Marszałek, Andrew Zisserman, Jianguo Zhang, M. Marszałek, Jiřı́ Matas and F. Schaffalitzky. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, Computational Statistics & Data Analysis, IEEE Transactions on Image Processing and Lecture notes in computer science.
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.