Kashyap Chitta
Kashyap Chitta
Max Planck Institute for Intelligent Systems, Tübingen
Verified email at tue.mpg.de - Homepage
Title
Cited by
Cited by
Year
Large-scale visual active learning with deep probabilistic ensembles
K Chitta, JM Alvarez, A Lesnikowski
arXiv preprint arXiv:1811.03575, 2018
132018
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
82020
Training Data Subset Search with Ensemble Active Learning
K Chitta, JM Alvarez, E Haussmann, C Farabet
arXiv preprint arXiv:1905.12737, 2019
7*2019
Adaptive semantic segmentation with a strategic curriculum of proxy labels
K Chitta, J Feng, M Hebert
arXiv preprint arXiv:1811.03542, 2018
62018
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
52020
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
42020
Learning Sampling Policies for Domain Adaptation
Y Patel, K Chitta, B Jasani
arXiv preprint arXiv:1805.07641, 2018
42018
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
32016
Label efficient visual abstractions for autonomous driving
A Behl, K Chitta, A Prakash, E Ohn-Bar, A Geiger
arXiv preprint arXiv:2005.10091, 2020
12020
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
12020
Targeted Kernel Networks: Faster Convolutions with Attentive Regularization
K Chitta
Proceedings of the European Conference on Computer Vision (ECCV) Workshops, 0-0, 2018
12018
Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences
MA Weis, K Chitta, Y Sharma, W Brendel, M Bethge, A Geiger, AS Ecker
arXiv preprint arXiv:2006.07034, 2020
2020
Deep Probabilistic Ensembles: Approximate Variational Inference through KL Regularization
K Chitta, JM Alvarez, A Lesnikowski
NeurIPS Workshop on Bayesian Deep Learning, 2018
2018
Supplementary Material for Learning Situational Driving
E Ohn-Bar, A Prakash, A Behl, K Chitta, A Geiger
Supplementary Material for Exploring Data Aggregation in Policy Learning for Vision-based Urban Autonomous Driving
A Prakash, A Behl, E Ohn-Bar, K Chitta, A Geiger
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