Shubham Tulsiani
- Computer Vision and Pattern Recognition top 0.5%
- Computational Mechanics top 1%
- Computer Graphics and Computer-Aided Design top 0.5%
- Aerospace Engineering top 5%
- Control and Systems Engineering top 5%
- Co-authors
- Jitendra MalikJoão CarreiraChristian HäneAbhishek KarLeonidas GuibasAbhinav GuptaChristoph LassnerJustin Johnson
- Topics
- Advanced Vision and Imaging (13 papers)Human Pose and Action Recognition (11 papers)Robot Manipulation and Learning (10 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligencePattern Recognition Letters2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Partner nations
- United StatesIsraelIndia
In The Last Decade
Shubham Tulsiani
32 papers receiving 1.6k citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Computer Vision and Pattern Recognition 1.2k
- Computational Mechanics 696
- Computer Graphics and Computer-Aided Design 442
- Aerospace Engineering 321
- Control and Systems Engineering 276
Countries citing papers authored by Shubham Tulsiani
This map shows the geographic impact of Shubham Tulsiani'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 Shubham Tulsiani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shubham Tulsiani more than expected).
Fields of papers citing papers by Shubham Tulsiani
This network shows the impact of papers produced by Shubham Tulsiani. 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 Shubham Tulsiani. The network helps show where Shubham Tulsiani may publish in the future.
Co-authorship network of co-authors of Shubham Tulsiani
This figure shows the co-authorship network connecting the top 25 collaborators of Shubham Tulsiani. A scholar is included among the top collaborators of Shubham Tulsiani 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 Shubham Tulsiani. Shubham Tulsiani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 33 | |
| 7 | 7 | |
| 8 | 15 | |
| 9 | 28 | |
| 10 | 3 | |
| 11 | 41 | |
| 12 | 0 | |
| 13 | Discovering Motor Programs by Recomposing Demonstrations | 9 |
| 14 | Visual Imitation Made Easy | 1 |
| 15 | See, Hear, Explore: Curiosity via Audio-Visual Association | 2 |
| 16 | Accelerating 3D deep learning with PyTorch3Dbreakdown → | 334 |
| 17 | 183 | |
| 18 | 184 | |
| 19 | 22 | |
| 20 | 23 |
About Shubham Tulsiani
Shubham Tulsiani is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Geology, having authored 36 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Vision and Imaging (13 papers), Human Pose and Action Recognition (11 papers) and Robot Manipulation and Learning (10 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (442 citations), Computer Vision and Pattern Recognition (1.2k citations) and Geology (246 citations). Shubham Tulsiani has collaborated with scholars based in United States, Israel and India. Frequent co-authors include Jitendra Malik, João Carreira, Christian Häne, Abhishek Kar, Leonidas Guibas, Abhinav Gupta, Christoph Lassner, Justin Johnson, Steve Branson and Nikhila Ravi. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition Letters and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.