Raphael Gontijo Lopes
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging
- Signal Processing
- Media Technology
- Co-authors
- Ali FarhadiMitchell WortsmanGabriel IlharcoHannaneh HajishirziHongseok NamkoongRebecca RoelofsSimon KornblithLudwig Schmidt
- Topics
- Advanced Neural Network Applications (3 papers)Advanced Image and Video Retrieval Techniques (2 papers)Video Surveillance and Tracking Methods (2 papers)
- Journals
- 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)arXiv (Cornell University)
- Partner nations
- United StatesGermanyJapan
In The Last Decade
Raphael Gontijo Lopes
5 papers receiving 263 citations
Hit Papers
Peers
Comparison fields: 5 of 47
- Artificial Intelligence 180
- Computer Vision and Pattern Recognition 179
- Radiology, Nuclear Medicine and Imaging 18
- Signal Processing 15
- Media Technology 10
Countries citing papers authored by Raphael Gontijo Lopes
This map shows the geographic impact of Raphael Gontijo Lopes'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 Raphael Gontijo Lopes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphael Gontijo Lopes more than expected).
Fields of papers citing papers by Raphael Gontijo Lopes
This network shows the impact of papers produced by Raphael Gontijo Lopes. 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 Raphael Gontijo Lopes. The network helps show where Raphael Gontijo Lopes may publish in the future.
Co-authorship network of co-authors of Raphael Gontijo Lopes
This figure shows the co-authorship network connecting the top 25 collaborators of Raphael Gontijo Lopes. A scholar is included among the top collaborators of Raphael Gontijo Lopes 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 Raphael Gontijo Lopes. Raphael Gontijo Lopes 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 | Robust fine-tuning of zero-shot modelsbreakdown → | 208 |
| 3 | Leveraging Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation. | 2 |
| 4 | Semi-Supervised Learning in Video Sequences for Urban Scene Segmentation | 5 |
| 5 | 55 |
About Raphael Gontijo Lopes
Raphael Gontijo Lopes is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases, having authored 5 papers that have together received 272 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (3 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Video Surveillance and Tracking Methods (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (179 citations), Artificial Intelligence (180 citations) and Health Informatics (3 citations). Raphael Gontijo Lopes has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Ali Farhadi, Mitchell Wortsman, Gabriel Ilharco, Hannaneh Hajishirzi, Hongseok Namkoong, Rebecca Roelofs, Simon Kornblith, Ludwig Schmidt, Jong Wook Kim and Chiori Hori. Their work appears in journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and arXiv (Cornell University).
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.