Kashyap Chitta

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 42

Top Topics

Object Representations

Autonomous Driving

Top Venues

Publications

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 (2024)
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 (2024)
Kashyap Chitta, Daniel Dauner, Andreas Geiger
SLEDGE: Synthesizing Simulation Environments for Driving Agents with Generative Models. CoRR (2024)
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 (2024)
Daniel Dauner, Marcel Hallgarten, Andreas Geiger, Kashyap Chitta
Parting with Misconceptions about Learning-based Vehicle Motion Planning. CoRL (2023)
Daniel Dauner, Marcel Hallgarten, Andreas Geiger, Kashyap Chitta
Parting with Misconceptions about Learning-based Vehicle Motion Planning. CoRR (2023)
Bernhard Jaeger, Kashyap Chitta, Andreas Geiger
Hidden Biases of End-to-End Driving Models. CoRR (2023)
Tim Schreier, Katrin Renz, Andreas Geiger, Kashyap Chitta
On Offline Evaluation of 3D Object Detection for Autonomous Driving. CoRR (2023)
Bernhard Jaeger, Kashyap Chitta, Andreas Geiger
Hidden Biases of End-to-End Driving Models. ICCV (2023)
Tim Schreier, Katrin Renz, Andreas Geiger, Kashyap Chitta
On Offline Evaluation of 3D Object Detection for Autonomous Driving. ICCV (Workshops) (2023)
Li Chen, Penghao Wu, Kashyap Chitta, Bernhard Jaeger, Andreas Geiger, Hongyang Li
End-to-end Autonomous Driving: Challenges and Frontiers. CoRR (2023)
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) (2023)
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 (2023)
Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata, Andreas Geiger
PlanT: Explainable Planning Transformers via Object-Level Representations. CoRL (2022)
Katrin Renz, Kashyap Chitta, Otniel-Bogdan Mercea, A. Sophia Koepke, Zeynep Akata, Andreas Geiger
PlanT: Explainable Planning Transformers via Object-Level Representations. CoRR (2022)
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)
Kashyap Chitta, Aditya Prakash, Bernhard Jäger, Zehao Yu, Katrin Renz, Andreas Geiger
TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving. CoRR (2022)
Niklas Hanselmann, Katrin Renz, Kashyap Chitta, Apratim Bhattacharyya, Andreas Geiger
KING: Generating Safety-Critical Driving Scenarios for Robust Imitation via Kinematics Gradients. CoRR (2022)
Kashyap Chitta, Jose M. Alvarez, Elmar Haussmann, Clément Farabet
Training Data Subset Search With Ensemble Active Learning. IEEE Trans. Intell. Transp. Syst. 23 (9) (2022)
Axel Sauer, Kashyap Chitta, Jens Müller, Andreas Geiger
Projected GANs Converge Faster. NeurIPS (2021)
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 (2021)
Kashyap Chitta, Aditya Prakash, Andreas Geiger
NEAT: Neural Attention Fields for End-to-End Autonomous Driving. CoRR (2021)
Aditya Prakash, Kashyap Chitta, Andreas Geiger
Multi-Modal Fusion Transformer for End-to-End Autonomous Driving. CoRR (2021)
Aditya Prakash, Kashyap Chitta, Andreas Geiger
Multi-Modal Fusion Transformer for End-to-End Autonomous Driving. CVPR (2021)
Axel Sauer, Kashyap Chitta, Jens Müller, Andreas Geiger
Projected GANs Converge Faster. CoRR (2021)
Kashyap Chitta, Aditya Prakash, Andreas Geiger
NEAT: Neural Attention Fields for End-to-End Autonomous Driving. ICCV (2021)
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 (2020)
Aseem Behl, Kashyap Chitta, Aditya Prakash, Eshed Ohn-Bar, Andreas Geiger
Label Efficient Visual Abstractions for Autonomous Driving. IROS (2020)
Elmar Haussmann, Michele Fenzi, Kashyap Chitta, Jan Ivanecky, Hanson Xu, Donna Roy, Akshita Mittel, Nicolas Koumchatzky, Clément Farabet, Jose M. Alvarez
Scalable Active Learning for Object Detection. CoRR (2020)
Aseem Behl, Kashyap Chitta, Aditya Prakash, Eshed Ohn-Bar, Andreas Geiger
Label Efficient Visual Abstractions for Autonomous Driving. CoRR (2020)
Eshed Ohn-Bar, Aditya Prakash, Aseem Behl, Kashyap Chitta, Andreas Geiger
Learning Situational Driving. CVPR (2020)
Elmar Haussmann, Michele Fenzi, Kashyap Chitta, Jan Ivanecky, Hanson Xu, Donna Roy, Akshita Mittel, Nicolas Koumchatzky, Clément Farabet, Jose M. Alvarez
Scalable Active Learning for Object Detection. IV (2020)
Kashyap Chitta, José M. Álvarez, Martial Hebert
Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions. WACV (2020)
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)
Kashyap Chitta, José M. Álvarez, Martial Hebert
Quadtree Generating Networks: Efficient Hierarchical Scene Parsing with Sparse Convolutions. CoRR (2019)
Kashyap Chitta, Jose M. Alvarez, Elmar Haussmann, Clément Farabet
Less is More: An Exploration of Data Redundancy with Active Dataset Subsampling. CoRR (2019)
Kashyap Chitta, Jose M. Alvarez, Adam Lesnikowski
Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization. CoRR (2018)
Kashyap Chitta
Targeted Kernel Networks: Faster Convolutions with Attentive Regularization. ECCV Workshops (4) (2018)
Yash Patel, Kashyap Chitta, Bhavan Jasani
Learning Sampling Policies for Domain Adaptation. CoRR (2018)
Kashyap Chitta, Jose M. Alvarez, Adam Lesnikowski
Large-Scale Visual Active Learning with Deep Probabilistic Ensembles. CoRR (2018)
Kashyap Chitta, Jianwei Feng, Martial Hebert
Adaptive Semantic Segmentation with a Strategic Curriculum of Proxy Labels. CoRR (2018)
Kashyap Chitta
Targeted Kernel Networks: Faster Convolutions with Attentive Regularization. CoRR (2018)