Dushyant Mehta
About
In The Last Decade
Dushyant Mehta
13 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 2.0k
- Human-Computer Interaction 649
- Control and Systems Engineering 474
- Computational Mechanics 358
- Biomedical Engineering 355
Countries citing papers authored by Dushyant Mehta
This map shows the geographic impact of Dushyant Mehta'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 Dushyant Mehta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dushyant Mehta more than expected).
Fields of papers citing papers by Dushyant Mehta
This network shows the impact of papers produced by Dushyant Mehta. 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 Dushyant Mehta. The network helps show where Dushyant Mehta may publish in the future.
Co-authorship network of co-authors of Dushyant Mehta
This figure shows the co-authorship network connecting the top 25 collaborators of Dushyant Mehta. A scholar is included among the top collaborators of Dushyant Mehta 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 Dushyant Mehta. Dushyant Mehta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Simple and Efficient Architectures for Semantic Segmentation | 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | Dushyant Mehta, Fatih Porikli et al. | 15 |
| 2 | Distilling Optimal Neural Networks: Rapid Search in Diverse Spaces | 2021 IEEE/CVF International Conference on Computer Vision (ICCV) | Bert Moons, Giovanni Mariani et al. | 20 |
| 3 | On implicit filter level sparsity in convolutional neural networks | Scholarworks@UNIST (Ulsan National Institute of Science and Technology) | Dushyant Mehta, Kwang In Kim et al. | 11 |
| 4 | XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera | MPG.PuRe (Max Planck Society) | Dushyant Mehta, Oleksandr Sotnychenko et al. | 14 |
| 5 | In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations | Ikhsanul Habibie, Weipeng Xu et al. | 84 | |
| 6 | MonoPerfCap | ACM Transactions on Graphics | Weipeng Xu, Avishek Chatterjee et al. | 139 |
| 7 | Single-Shot Multi-person 3D Pose Estimation from Monocular RGB | Dushyant Mehta, Oleksandr Sotnychenko et al. | 246 | |
| 8 | GANerated Hands for Real-Time 3D Hand Tracking from Monocular RGB breakdown → | Franziska Mueller, Florian Bernard et al. | 317 | |
| 9 | Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision breakdown → | Dushyant Mehta, Helge Rhodin et al. | 609 | |
| 10 | Single-Shot Multi-Person 3D Body Pose Estimation From Monocular RGB Input | Max Planck Digital Library | Dushyant Mehta, Oleksandr Sotnychenko et al. | 7 |
| 11 | VNect breakdown → | ACM Transactions on Graphics | Dushyant Mehta, Srinath Sridhar et al. | 690 |
| 12 | Real-Time Hand Tracking Under Occlusion from an Egocentric RGB-D Sensor | Franziska Mueller, Dushyant Mehta et al. | 64 | |
| 13 | Monocular 3D Human Pose Estimation Using Transfer Learning and Improved CNN Supervision | arXiv (Cornell University) | Dushyant Mehta, Helge Rhodin et al. | 17 |
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.