Arash Vahdat
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- Human Pose and Action Recognition 10
- Advanced Image and Video Retrieval Techniques 9
- Video Analysis and Summarization 8
- Generative Adversarial Networks and Image Synthesis 6
- Advanced Neural Network Applications 4
- Video Surveillance and Tracking Methods 4
- Face and Expression Recognition 3
- Artificial Intelligence top 2%
- Domain Adaptation and Few-Shot Learning 7
- Human-Computer Interaction top 10%
- Media Technology top 10%
Arash Vahdat
31 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Computer Vision and Pattern Recognition 681
- Artificial Intelligence 601
- Human-Computer Interaction 35
- Media Technology 44
- Computer Graphics and Computer-Aided Design 16
Countries citing papers authored by Arash Vahdat
This map shows the geographic impact of Arash Vahdat'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 Arash Vahdat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arash Vahdat more than expected).
Fields of papers citing papers by Arash Vahdat
This network shows the impact of papers produced by Arash Vahdat. 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 Arash Vahdat. The network helps show where Arash Vahdat may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Arash Vahdat, 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 | 2025 | 14 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 5 | |
| 4 | State-specific protein–ligand complex structure prediction with a multiscale deep generative modelbreakdown → | 2024 | 66 |
| 5 | 2024 | 2 | |
| 6 | PhysDiff: Physics-Guided Human Motion Diffusion Modelbreakdown → | 2023 | 98 |
| 7 | A-ViT: Adaptive Tokens for Efficient Vision Transformerbreakdown → | 2022 | 165 |
| 8 | 2022 | 0 | |
| 9 | See through Gradients: Image Batch Recovery via GradInversionbreakdown → | 2021 | 254 |
| 10 | Undirected Graphical Models as Approximate Posteriors | 2020 | 1 |
| 11 | NVAE: A Deep Hierarchical Variational Autoencoder | 2020 | 18 |
| 12 | DVAE++: Discrete Variational Autoencoders with Overlapping Transformations | 2018 | 2 |
| 13 | DVAE#: Discrete Variational Autoencoders with Relaxed Boltzmann Priors | 2018 | 3 |
| 14 | Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks | 2017 | 68 |
| 15 | Latent Maximum Margin Clustering | 2013 | 15 |
| 16 | 2013 | 11 | |
| 17 | Kernel Latent SVM for Visual Recognition | 2012 | 13 |
| 18 | 2010 | 2 | |
| 19 | 2009 | 1 | |
| 20 | 1995 | 10 |
About Arash Vahdat
Arash Vahdat is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, General Social Sciences, Computer Graphics and Computer-Aided Design and Immunology and Allergy, having authored 32 papers that have together received 1.2k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (10 papers), Advanced Image and Video Retrieval Techniques (9 papers), Video Analysis and Summarization (8 papers), Domain Adaptation and Few-Shot Learning (7 papers), Generative Adversarial Networks and Image Synthesis (6 papers), Advanced Neural Network Applications (4 papers), Video Surveillance and Tracking Methods (4 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (681 citations), Artificial Intelligence (601 citations), Human-Computer Interaction (35 citations), Media Technology (44 citations) and Computer Graphics and Computer-Aided Design (16 citations). Arash Vahdat has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Jan Kautz, Pavlo Molchanov, Hongxu Yin, José M. Alvarez, Arun Mallya, Greg Mori, Mani Ranjbar, Sifei Liu, Xiaolong Wang and Wonmin Byeon. Their work appears in journals such as Communications Earth & Environment, FEBS Letters, Nature Machine Intelligence, Machine Vision and Applications and Computer Vision and Image Understanding.
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.