Kashyap Chitta

1.5k total citations · 2 hit papers
12 papers, 599 citations indexed

About

Kashyap Chitta is a scholar working on Computer Vision and Pattern Recognition, Automotive Engineering and Artificial Intelligence. According to data from OpenAlex, Kashyap Chitta has authored 12 papers receiving a total of 599 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 5 papers in Automotive Engineering and 2 papers in Artificial Intelligence. Recurrent topics in Kashyap Chitta's work include Advanced Neural Network Applications (7 papers), Autonomous Vehicle Technology and Safety (5 papers) and Video Surveillance and Tracking Methods (2 papers). Kashyap Chitta is often cited by papers focused on Advanced Neural Network Applications (7 papers), Autonomous Vehicle Technology and Safety (5 papers) and Video Surveillance and Tracking Methods (2 papers). Kashyap Chitta collaborates with scholars based in Germany, Hong Kong and United States. Kashyap Chitta's co-authors include Andreas Geiger, Bernhard Jaeger, Aditya Prakash, Zehao Yu, Aditya Prakash, Penghao Wu, Hongyang Li, Li Chen, Aseem Behl and Eshed Ohn-Bar and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and Rare & Special e-Zone (The Hong Kong University of Science and Technology).

In The Last Decade

Kashyap Chitta

11 papers receiving 572 citations

Hit Papers

TransFuser: Imitation With Transformer-Based Sensor Fusio... 2022 2026 2023 2024 2022 2024 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kashyap Chitta Germany 7 314 306 184 94 73 12 599
Xiaosong Jia China 6 263 0.8× 268 0.9× 151 0.8× 68 0.7× 48 0.7× 11 544
Yihan Hu China 4 263 0.8× 169 0.6× 102 0.6× 44 0.5× 87 1.2× 8 470
Chonghao Sima China 4 232 0.7× 170 0.6× 98 0.5× 45 0.5× 52 0.7× 5 428
Bernhard Jaeger Germany 4 165 0.5× 179 0.6× 113 0.6× 51 0.5× 44 0.6× 4 365
Aseem Behl Germany 6 328 1.0× 148 0.5× 125 0.7× 43 0.5× 80 1.1× 8 519
Peter Ondrúška United Kingdom 9 202 0.6× 188 0.6× 99 0.5× 73 0.8× 99 1.4× 13 429
Sihai Tang United States 9 393 1.3× 204 0.7× 161 0.9× 70 0.7× 95 1.3× 17 704
Chiyu Dong United States 11 194 0.6× 303 1.0× 81 0.4× 156 1.7× 93 1.3× 15 432
Jürgen Wiest Germany 9 168 0.5× 274 0.9× 139 0.8× 79 0.8× 81 1.1× 12 456
Tingxiang Fan Hong Kong 12 337 1.1× 113 0.4× 188 1.0× 124 1.3× 194 2.7× 16 576

Countries citing papers authored by Kashyap Chitta

Since Specialization
Citations

This map shows the geographic impact of Kashyap Chitta'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 Kashyap Chitta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kashyap Chitta more than expected).

Fields of papers citing papers by Kashyap Chitta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kashyap Chitta. 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 Kashyap Chitta. The network helps show where Kashyap Chitta may publish in the future.

Co-authorship network of co-authors of Kashyap Chitta

This figure shows the co-authorship network connecting the top 25 collaborators of Kashyap Chitta. A scholar is included among the top collaborators of Kashyap Chitta 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 Kashyap Chitta. Kashyap Chitta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
Chen, Li, Penghao Wu, Kashyap Chitta, et al.. (2024). End-to-End Autonomous Driving: Challenges and Frontiers. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(12). 10164–10183. 143 indexed citations breakdown →
2.
Yang, Jiazhi, Shenyuan Gao, Li Chen, et al.. (2024). Generalized Predictive Model for Autonomous Driving. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 14662–14672. 15 indexed citations
3.
Chitta, Kashyap, Andreas Geiger, Igor Gilitschenski, et al.. (2024). NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking. 28706–28719.
4.
Chitta, Kashyap, et al.. (2024). Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability. 91560–91596. 1 indexed citations
5.
Jaeger, Bernhard, Kashyap Chitta, & Andreas Geiger. (2023). Hidden Biases of End-to-End Driving Models. 8206–8215. 30 indexed citations
6.
Geiger, Andreas, et al.. (2023). On Offline Evaluation of 3D Object Detection for Autonomous Driving. 4086–4091. 5 indexed citations
7.
Chitta, Kashyap, et al.. (2022). TransFuser: Imitation With Transformer-Based Sensor Fusion for Autonomous Driving. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(11). 12878–12895. 189 indexed citations breakdown →
8.
Chitta, Kashyap, Aditya Prakash, & Andreas Geiger. (2021). NEAT: Neural Attention Fields for End-to-End Autonomous Driving. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 15773–15783. 132 indexed citations
9.
Prakash, Aditya, Aseem Behl, Eshed Ohn-Bar, Kashyap Chitta, & Andreas Geiger. (2020). Exploring Data Aggregation in Policy Learning for Vision-Based Urban Autonomous Driving. 11760–11770. 46 indexed citations
10.
Ohn-Bar, Eshed, et al.. (2020). Learning Situational Driving. 11293–11302. 35 indexed citations
11.
Chitta, Kashyap, José M. Alvarez, Elmar Haußmann, & Clément Farabet. (2019). Less is More: An Exploration of Data Redundancy with Active Dataset Subsampling.. arXiv (Cornell University). 2 indexed citations
12.
Chitta, Kashyap, et al.. (2016). A reduced region of interest based approach for facial expression recognition from static images. 2806–2809. 1 indexed citations

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.

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