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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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Journal Articles
- 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)- 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) - 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)
Conference and Workshop Papers
- 2024
- [c16]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 - [c15]Kashyap Chitta, Daniel Dauner, Andreas Geiger:
SLEDGE: Synthesizing Driving Environments with Generative Models and Rule-Based Traffic. ECCV (4) 2024: 57-74 - 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 - 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 - 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 - 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 - 2018
- [c1]Kashyap Chitta:
Targeted Kernel Networks: Faster Convolutions with Attentive Regularization. ECCV Workshops (4) 2018: 379-397
Informal and Other Publications
- 2024
- [i25]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) - [i24]Kashyap Chitta, Daniel Dauner, Andreas Geiger:
SLEDGE: Synthesizing Simulation Environments for Driving Agents with Generative Models. CoRR abs/2403.17933 (2024) - [i23]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) - [i22]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) - 2023
- [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
- [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
- [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
- [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) - 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
- [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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