Mahyar Najibi
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- Advanced Image and Video Retrieval Techniques 3
- Advanced Neural Network Applications 3
- Generative Adversarial Networks and Image Synthesis 2
- Human Pose and Action Recognition 2
- Media Technology top 5%
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- Domain Adaptation and Few-Shot Learning 3
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- 3D Shape Modeling and Analysis 2
- Sparse and Compressive Sensing Techniques 1
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- Human Motion and Animation 1
- Co-authors
- Larry S. DavisBharat SinghSer-Nam LimBor-Chun ChenAbhinav ShrivastavaXintong HanPeng ZhouDragomir Anguelov
- Journals
- IEEE Transactions on Image Processing (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesGermanyIran
In The Last Decade
Mahyar Najibi
9 papers receiving 192 citations
Peers
Comparison fields: 5 of 36
- Computer Vision and Pattern Recognition 179
- Media Technology 59
- Biophysics 12
- Computer Graphics and Computer-Aided Design 7
- Artificial Intelligence 47
Countries citing papers authored by Mahyar Najibi
This map shows the geographic impact of Mahyar Najibi'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 Mahyar Najibi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahyar Najibi more than expected).
Fields of papers citing papers by Mahyar Najibi
This network shows the impact of papers produced by Mahyar Najibi. 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 Mahyar Najibi. The network helps show where Mahyar Najibi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mahyar Najibi, 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 | 2023 | 13 | |
| 2 | 2023 | 7 | |
| 3 | 2023 | 8 | |
| 4 | 2020 | 95 | |
| 5 | Batch-wise Logit-Similarity: Generalizing Logit-Squeezing and Label-Smoothing. | 2019 | 1 |
| 6 | 2019 | 29 | |
| 7 | Soft Sampling for Robust Object Detection. | 2018 | 1 |
| 8 | 2018 | 38 | |
| 9 | 2015 | 3 |
About Mahyar Najibi
Mahyar Najibi is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics, having authored 9 papers that have together received 195 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Human Pose and Action Recognition (2 papers), 3D Shape Modeling and Analysis (2 papers), Sparse and Compressive Sensing Techniques (1 paper) and Human Motion and Animation (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (179 citations), Media Technology (59 citations) and Biophysics (12 citations). Mahyar Najibi has collaborated with scholars based in United States, Germany and Iran. Frequent co-authors include Larry S. Davis, Bharat Singh, Ser-Nam Lim, Bor-Chun Chen, Abhinav Shrivastava, Xintong Han, Peng Zhou, Dragomir Anguelov, Charles R. Qi and Yin Zhou. Their work appears in journals such as IEEE Transactions on Image Processing, arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.