| Multi-modal fusion transformer for end-to-end autonomous driving A Prakash*, K Chitta*, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 200 | 2021 |
| Scalable active learning for object detection E Haussmann, M Fenzi, K Chitta, J Ivanecky, H Xu, D Roy, A Mittel, ... 2020 IEEE intelligent vehicles symposium (iv), 1430-1435, 2020 | 81 | 2020 |
| Projected gans converge faster A Sauer, K Chitta, J Müller, A Geiger Advances in Neural Information Processing Systems 34, 17480-17492, 2021 | 67 | 2021 |
| Neat: Neural attention fields for end-to-end autonomous driving K Chitta*, A Prakash*, A Geiger Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 52 | 2021 |
| Exploring data aggregation in policy learning for vision-based urban autonomous driving A Prakash, A Behl, E Ohn-Bar, K Chitta, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 49 | 2020 |
| Learning situational driving E Ohn-Bar, A Prakash, A Behl, K Chitta, A Geiger Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 47 | 2020 |
| Training Data Subset Search With Ensemble Active Learning K Chitta, JM Álvarez, E Haussmann, C Farabet IEEE Transactions on Intelligent Transportation Systems, 2021 | 31* | 2021 |
| Label efficient visual abstractions for autonomous driving A Behl*, K Chitta*, A Prakash, E Ohn-Bar, A Geiger 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 26 | 2020 |
| Large-scale visual active learning with deep probabilistic ensembles K Chitta, JM Alvarez, A Lesnikowski arXiv preprint arXiv:1811.03575, 2018 | 25 | 2018 |
| Benchmarking Unsupervised Object Representations for Video Sequences MA Weis, K Chitta, Y Sharma, W Brendel, M Bethge, A Geiger, AS Ecker Journal of Machine Learning Research 22 (183), 1-61, 2021 | 24* | 2021 |
| Transfuser: Imitation with transformer-based sensor fusion for autonomous driving K Chitta, A Prakash, B Jaeger, Z Yu, K Renz, A Geiger IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 18 | 2022 |
| Adaptive semantic segmentation with a strategic curriculum of proxy labels K Chitta, J Feng, M Hebert arXiv preprint arXiv:1811.03542, 2018 | 12 | 2018 |
| Quadtree generating networks: Efficient hierarchical scene parsing with sparse convolutions K Chitta, JM Alvarez, M Hebert Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2020 | 11 | 2020 |
| King: Generating safety-critical driving scenarios for robust imitation via kinematics gradients N Hanselmann, K Renz, K Chitta, A Bhattacharyya, A Geiger Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 6 | 2022 |
| A reduced region of interest based approach for facial expression recognition from static images K Chitta, NN Sajjan 2016 IEEE Region 10 Conference (TENCON), 2806-2809, 2016 | 5 | 2016 |
| Learning Sampling Policies for Domain Adaptation Y Patel*, K Chitta*, B Jasani* arXiv preprint arXiv:1805.07641, 2018 | 4 | 2018 |
| Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization K Chitta, JM Alvarez, A Lesnikowski NeurIPS Workshop on Bayesian Deep Learning, 2018 | 2 | 2018 |
| Targeted Kernel Networks: Faster Convolutions with Attentive Regularization K Chitta Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018 | 2 | 2018 |
| Supplementary material for multi-modal fusion transformer for end-to-end autonomous driving A Prakash*, K Chitta*, A Geiger | 1 | 2021 |
| PlanT: Explainable Planning Transformers via Object-Level Representations K Renz, K Chitta, OB Mercea, A Koepke, Z Akata, A Geiger arXiv preprint arXiv:2210.14222, 2022 | | 2022 |
Andreas GeigerProfessor of Computer Science, University of Tübingen and Tübingen AI Center確認したメール アドレス: uni-tuebingen.de
