Aseem Behl
Aseem Behl
Max Planck Institute for Intelligent Systems
Verified email at tuebingen.mpg.de - Homepage
Title
Cited by
Cited by
Year
Computer vision for autonomous vehicles: Problems, datasets and state of the art
J Janai, F Güney, A Behl, A Geiger
Arxiv, arXiv: 1704.05519, 2017
2212017
Bounding boxes, segmentations and object coordinates: How important is recognition for 3d scene flow estimation in autonomous driving scenarios?
A Behl, O Hosseini Jafari, S Karthik Mustikovela, H Abu Alhaija, C Rother, ...
Proceedings of the IEEE International Conference on Computer Vision, 2574-2583, 2017
662017
Flownet3d: Learning scene flow in 3d point clouds
X Liu, CR Qi, LJ Guibas
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
422019
Pointflownet: Learning representations for rigid motion estimation from point clouds
A Behl, D Paschalidou, S Donné, A Geiger
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
21*2019
Optimizing average precision using weakly supervised data
A Behl, CV Jawahar, M Pawan Kumar
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014
182014
Learning to rank using high-order information
PK Dokania, A Behl, CV Jawahar, MP Kumar
European Conference on Computer Vision, 609-623, 2014
82014
A Corpus Linguistic Study of Bollywood Song Lyrics in the Framework of Complex Network Theory
A Behl, M Choudhury
International Conference on Natural Language Processing, 2011
72011
Monocular vision based road marking recognition for driver assistance and safety
M Sukhwani, S Singh, A Goyal, A Behl, P Mohapatra, BK Bharti, ...
2014 IEEE International Conference on Vehicular Electronics and Safety, 11-16, 2014
22014
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
12020
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
12020
Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art
J Janai, F Güney, A Behl, A Geiger
Foundations and Trends® in Computer Graphics and Vision 12 (1–3), 1-308, 2020
2020
Label Efficient Visual Abstractions for Autonomous Driving
A Behl, K Chitta, A Prakash, E Ohn-Bar, A Geiger
arXiv preprint arXiv:2005.10091, 2020
2020
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
Supplementary Material for Bounding Boxes, Segmentations and Object Coordinates: How Important is Recognition for 3D Scene Flow Estimation in Autonomous Driving Scenarios?
A Behl, OH Jafari, SK Mustikovela, HA Alhaija, C Rother, A Geiger
Optimizing Average Precision using Weakly Supervised Data
MP Kumar
Technical Report: Learning to Rank using High-Order Information
PK Dokania, A Behl, CV Jawahar, MP Kumar
Supplementary Material-Optimizing Average Precision using Weakly Supervised Data
A Behl, CV Jawahar, MP Kumar
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