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ORCIDKashyap Chitta
Person information
- affiliation: University of Tübingen, Autonomous Vision Group, Germany
- affiliation: Max Planck Institute for Intelligent Systems, Tübingen, Germany
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2020 – today
- 2026
[i38]Xunjiang Gu, Kashyap Chitta, Mahsa Golchoubian, Vladimir Suplin, Igor Gilitschenski:
Dynamics Distillation for Efficient and Transferable Control Learning. CoRR abs/2605.01516 (2026)- [i37]Daniel Dauner, Valentin Charraut, Bastian Berle, Tianyu Li, Long Nguyen, Jiabao Wang, Changhui Jing, Maximilian Igl, Holger Caesar, Boris Ivanovic, Yiyi Liao, Andreas Geiger, Kashyap Chitta:
123D: Unifying Multi-Modal Autonomous Driving Data at Scale. CoRR abs/2605.08084 (2026) - [i36]Xinglong Sun, Kevin Xie, Jenny Schmalfuss, Despoina Paschalidou, Xiuming Zhang, Sanja Fidler, Kashyap Chitta, José M. Álvarez:
DriveJudge: Rethinking Autonomous Driving Evaluation with Vision-Language Models. CoRR abs/2606.17362 (2026) - [i35]Tianyu Li, Li Chen, Caojun Wang, Haochen Liu, Kashyap Chitta, Zhenjie Yang, Yuhang Lu, Naisheng Ye, Yihang Qiu, Yufei Wang, Luoxi Zou, Jiaxin Peng, Jin Pan, Zhaoyu Su, Andrei Bursuc, Shengbo Eben Li, Andreas Geiger, Peng Su, Hongyang Li:
World Engine: Towards the Era of Post-Training for Autonomous Driving. CoRR abs/2606.19836 (2026) - 2025
- [c20]Jiazhi Yang, Kashyap Chitta, Shenyuan Gao, Long Chen, Yuqian Shao, Xiaosong Jia, Hongyang Li, Andreas Geiger, Xiangyu Yue, Li Chen:
ReSim: Reliable World Simulation for Autonomous Driving. NeurIPS 2025 - [i34]Chonghao Sima, Kashyap Chitta, Zhiding Yu, Shiyi Lan, Ping Luo, Andreas Geiger, Hongyang Li, José M. Álvarez:
Centaur: Robust End-to-End Autonomous Driving with Test-Time Training. CoRR abs/2503.11650 (2025) - [i33]Bernhard Jaeger
, Daniel Dauner, Jens Beißwenger, Simon Gerstenecker, Kashyap Chitta, Andreas Geiger:
CaRL: Learning Scalable Planning Policies with Simple Rewards. CoRR abs/2504.17838 (2025) - [i32]Wei Cao, Marcel Hallgarten, Tianyu Li, Daniel Dauner, Xunjiang Gu, Caojun Wang, Yakov Miron, Marco Aiello, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta:
Pseudo-Simulation for Autonomous Driving. CoRR abs/2506.04218 (2025) - [i31]Jiazhi Yang, Kashyap Chitta, Shenyuan Gao, Long Chen, Yuqian Shao, Xiaosong Jia, Hongyang Li, Andreas Geiger, Xiangyu Yue, Li Chen:
ReSim: Reliable World Simulation for Autonomous Driving. CoRR abs/2506.09981 (2025) - [i30]Yixuan Pan, Ruoyi Qiao, Li Chen, Kashyap Chitta, Liang Pan, Haoguang Mai, Qingwen Bu, Hao Zhao, Cunyuan Zheng, Ping Luo, Hongyang Li:
Agility Meets Stability: Versatile Humanoid Control with Heterogeneous Data. CoRR abs/2511.17373 (2025) - [i29]Shihao Li, Naisheng Ye, Tianyu Li, Kashyap Chitta, Tuo An, Peng Su, Boyang Wang, Haiou Liu, Chen Lv, Hongyang Li:
Optimization-Guided Diffusion for Interactive Scene Generation. CoRR abs/2512.07661 (2025) - [i28]Shuhan Tan, Kashyap Chitta, Yuxiao Chen, Ran Tian, Yurong You, Yan Wang, Wenjie Luo, Yulong Cao, Philipp Krähenbühl, Marco Pavone, Boris Ivanovic:
Latent Chain-of-Thought World Modeling for End-to-End Driving. CoRR abs/2512.10226 (2025) - [i27]Long Nguyen, Micha Fauth, Bernhard Jaeger, Daniel Dauner, Maximilian Igl, Andreas Geiger, Kashyap Chitta:
LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving. CoRR abs/2512.20563 (2025) - 2024
- [j4]Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, Hongyang Li:
End-to-End Autonomous Driving: Challenges and Frontiers. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 10164-10183 (2024) - [c19]Jiazhi Yang, Shenyuan Gao, Yihang Qiu, Li Chen, Tianyu Li, Bo Dai, Kashyap Chitta, Penghao Wu, Jia Zeng, Ping Luo, Jun Zhang, Andreas Geiger, Yu Qiao, Hongyang Li:
Generalized Predictive Model for Autonomous Driving. CVPR 2024: 14662-14672 - [c18]Kashyap Chitta, Daniel Dauner, Andreas Geiger:
SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic. ECCV (4) 2024: 57-74 - [c17]Chonghao Sima, Katrin Renz, Kashyap Chitta, Li Chen, Hanxue Zhang, Chengen Xie, Jens Beißwenger, Ping Luo, Andreas Geiger, Hongyang Li:
DriveLM: Driving with Graph Visual Question Answering. ECCV (52) 2024: 256-274 - [c16]Daniel Dauner, Marcel Hallgarten, Tianyu Li, Xinshuo Weng, Zhiyu Huang, Zetong Yang, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta:
NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking. NeurIPS 2024 - [c15]Shenyuan Gao, Jiazhi Yang, Li Chen, Kashyap Chitta, Yihang Qiu, Andreas Geiger, Jun Zhang, Hongyang Li:
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability. NeurIPS 2024 - [i26]Jiazhi Yang, Shenyuan Gao, Yihang Qiu, Li Chen, Tianyu Li, Bo Dai, Kashyap Chitta, Penghao Wu, Jia Zeng, Ping Luo, Jun Zhang, Andreas Geiger, Yu Qiao, Hongyang Li:
Generalized Predictive Model for Autonomous Driving. CoRR abs/2403.09630 (2024) - [i25]Kashyap Chitta, Daniel Dauner, Andreas Geiger:
SLEDGE: Synthesizing Simulation Environments for Driving Agents with Generative Models. CoRR abs/2403.17933 (2024) - [i24]Shenyuan Gao, Jiazhi Yang, Li Chen, Kashyap Chitta, Yihang Qiu, Andreas Geiger, Jun Zhang, Hongyang Li:
Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability. CoRR abs/2405.17398 (2024) - [i23]Daniel Dauner, Marcel Hallgarten, Tianyu Li, Xinshuo Weng, Zhiyu Huang, Zetong Yang, Hongyang Li, Igor Gilitschenski, Boris Ivanovic, Marco Pavone, Andreas Geiger, Kashyap Chitta:
NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking. CoRR abs/2406.15349 (2024) - [i22]Julian Zimmerlin, Jens Beißwenger, Bernhard Jaeger, Andreas Geiger, Kashyap Chitta:
Hidden Biases of End-to-End Driving Datasets. CoRR abs/2412.09602 (2024) - 2023
- [j3]Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, Andreas Geiger:
TransFuser: Imitation With Transformer-Based Sensor Fusion for Autonomous Driving. IEEE Trans. Pattern Anal. Mach. Intell. 45(11): 12878-12895 (2023) - [c14]Daniel Dauner, Marcel Hallgarten, Andreas Geiger, Kashyap Chitta:
Parting with Misconceptions about Learning-based Vehicle Motion Planning. CoRL 2023: 1268-1281 - [c13]Bernhard Jaeger, Kashyap Chitta, Andreas Geiger:
Hidden Biases of End-to-End Driving Models. ICCV 2023: 8206-8215 - [c12]Tim Schreier, Katrin Renz, Andreas Geiger, Kashyap Chitta:
On Offline Evaluation of 3D Object Detection for Autonomous Driving. ICCV (Workshops) 2023: 4086-4091 - [i21]Bernhard Jaeger, Kashyap Chitta, Andreas Geiger:
Hidden Biases of End-to-End Driving Models. CoRR abs/2306.07957 (2023) - [i20]Daniel Dauner, Marcel Hallgarten, Andreas Geiger, Kashyap Chitta:
Parting with Misconceptions about Learning-based Vehicle Motion Planning. CoRR abs/2306.07962 (2023) - [i19]Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, Hongyang Li:
End-to-end Autonomous Driving: Challenges and Frontiers. CoRR abs/2306.16927 (2023) - [i18]Tim Schreier, Katrin Renz, Andreas Geiger, Kashyap Chitta:
On Offline Evaluation of 3D Object Detection for Autonomous Driving. CoRR abs/2308.12779 (2023) - [i17]Chonghao Sima, Katrin Renz, Kashyap Chitta, Li Chen, Hanxue Zhang, Chengen Xie, Ping Luo, Andreas Geiger, Hongyang Li:
DriveLM: Driving with Graph Visual Question Answering. CoRR abs/2312.14150 (2023) - 2022
- [j2]Kashyap Chitta, José M. Álvarez, Elmar Haussmann, Clément Farabet:
Training Data Subset Search With Ensemble Active Learning. IEEE Trans. Intell. Transp. Syst. 23(9): 14741-14752 (2022) - [c11]Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata, Andreas Geiger:
PlanT: Explainable Planning Transformers via Object-Level Representations. CoRL 2022: 459-470 - [c10]Niklas Hanselmann, Katrin Renz, Kashyap Chitta, Apratim Bhattacharyya, Andreas Geiger:
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients. ECCV (38) 2022: 335-352 - [i16]Niklas Hanselmann, Katrin Renz, Kashyap Chitta, Apratim Bhattacharyya, Andreas Geiger:
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients. CoRR abs/2204.13683 (2022) - [i15]Kashyap Chitta, Aditya Prakash, Bernhard Jaeger, Zehao Yu, Katrin Renz, Andreas Geiger:
TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving. CoRR abs/2205.15997 (2022) - [i14]Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata, Andreas Geiger:
PlanT: Explainable Planning Transformers via Object-Level Representations. CoRR abs/2210.14222 (2022) - 2021
- [j1]Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker:
Benchmarking Unsupervised Object Representations for Video Sequences. J. Mach. Learn. Res. 22: 183:1-183:61 (2021) - [c9]Aditya Prakash, Kashyap Chitta, Andreas Geiger:
Multi-Modal Fusion Transformer for End-to-End Autonomous Driving. CVPR 2021: 7077-7087 - [c8]Kashyap Chitta, Aditya Prakash, Andreas Geiger:
NEAT: Neural Attention Fields for End-to-End Autonomous Driving. ICCV 2021: 15773-15783 - [c7]Axel Sauer, Kashyap Chitta, Jens Müller, Andreas Geiger:
Projected GANs Converge Faster. NeurIPS 2021: 17480-17492 - [i13]Aditya Prakash, Kashyap Chitta, Andreas Geiger:
Multi-Modal Fusion Transformer for End-to-End Autonomous Driving. CoRR abs/2104.09224 (2021) - [i12]Kashyap Chitta, Aditya Prakash, Andreas Geiger:
NEAT: Neural Attention Fields for End-to-End Autonomous Driving. CoRR abs/2109.04456 (2021) - [i11]Axel Sauer, Kashyap Chitta, Jens Müller, Andreas Geiger:
Projected GANs Converge Faster. CoRR abs/2111.01007 (2021) - 2020
- [c6]Eshed Ohn-Bar, Aditya Prakash, Aseem Behl, Kashyap Chitta, Andreas Geiger:
Learning Situational Driving. CVPR 2020: 11293-11302 - [c5]Aditya Prakash, Aseem Behl, Eshed Ohn-Bar, Kashyap Chitta, Andreas Geiger:
Exploring Data Aggregation in Policy Learning for Vision-Based Urban Autonomous Driving. CVPR 2020: 11760-11770 - [c4]Aseem Behl, Kashyap Chitta, Aditya Prakash, Eshed Ohn-Bar, Andreas Geiger:
Label Efficient Visual Abstractions for Autonomous Driving. IROS 2020: 2338-2345 - [c3]Elmar Haussmann, Michele Fenzi, Kashyap Chitta, Jan Ivanecky, Hanson Xu, Donna Roy, Akshita Mittel, Nicolas Koumchatzky, Clément Farabet, José M. Álvarez:
Scalable Active Learning for Object Detection. IV 2020: 1430-1435 - [c2]Kashyap Chitta, José M. Álvarez, Martial Hebert:
Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions. WACV 2020: 2009-2018 - [i10]Elmar Haussmann, Michele Fenzi, Kashyap Chitta, Jan Ivanecky, Hanson Xu, Donna Roy, Akshita Mittel, Nicolas Koumchatzky, Clément Farabet, José M. Álvarez:
Scalable Active Learning for Object Detection. CoRR abs/2004.04699 (2020) - [i9]Aseem Behl, Kashyap Chitta, Aditya Prakash, Eshed Ohn-Bar, Andreas Geiger:
Label Efficient Visual Abstractions for Autonomous Driving. CoRR abs/2005.10091 (2020) - [i8]Marissa A. Weis, Kashyap Chitta, Yash Sharma, Wieland Brendel, Matthias Bethge, Andreas Geiger, Alexander S. Ecker:
Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences. CoRR abs/2006.07034 (2020)
2010 – 2019
- 2019
- [i7]Kashyap Chitta, José M. Álvarez, Elmar Haussmann, Clément Farabet:
Less is More: An Exploration of Data Redundancy with Active Dataset Subsampling. CoRR abs/1905.12737 (2019) - [i6]Kashyap Chitta, José M. Álvarez, Martial Hebert:
Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions. CoRR abs/1907.11821 (2019) - 2018
- [c1]Kashyap Chitta:
Targeted Kernel Networks: Faster Convolutions with Attentive Regularization. ECCV Workshops (4) 2018: 379-397 - [i5]Yash Patel, Kashyap Chitta, Bhavan Jasani:
Learning Sampling Policies for Domain Adaptation. CoRR abs/1805.07641 (2018) - [i4]Kashyap Chitta:
Targeted Kernel Networks: Faster Convolutions with Attentive Regularization. CoRR abs/1806.00523 (2018) - [i3]Kashyap Chitta, José M. Álvarez, Adam Lesnikowski:
Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization. CoRR abs/1811.02640 (2018) - [i2]Kashyap Chitta, Jianwei Feng, Martial Hebert:
Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels. CoRR abs/1811.03542 (2018) - [i1]Kashyap Chitta, José M. Álvarez, Adam Lesnikowski:
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles. CoRR abs/1811.03575 (2018)
Coauthor Index
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