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Rares Ambrus
Rares Ambrus
Toyota Research Institute (TRI)
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Titel
Zitiert von
Zitiert von
Jahr
3d packing for self-supervised monocular depth estimation
V Guizilini, R Ambrus, S Pillai, A Raventos, A Gaidon
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
8232020
Is pseudo-lidar needed for monocular 3d object detection?
D Park, R Ambrus, V Guizilini, J Li, A Gaidon
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
3582021
Probabilistic 3D multi-modal, multi-object tracking for autonomous driving
H Chiu, J Li, R Ambruş, J Bohg
2021 IEEE international conference on robotics and automation (ICRA), 14227 …, 2021
2832021
Semantically-guided representation learning for self-supervised monocular depth
V Guizilini, R Hou, J Li, R Ambrus, A Gaidon
arXiv preprint arXiv:2002.12319, 2020
2762020
The strands project: Long-term autonomy in everyday environments
N Hawes, C Burbridge, F Jovan, L Kunze, B Lacerda, L Mudrova, J Young, ...
IEEE Robotics & Automation Magazine 24 (3), 146-156, 2017
2642017
Superdepth: Self-supervised, super-resolved monocular depth estimation
S Pillai, R Ambruş, A Gaidon
2019 International Conference on Robotics and Automation (ICRA), 9250-9256, 2019
2592019
Simple-bev: What really matters for multi-sensor bev perception?
AW Harley, Z Fang, J Li, R Ambrus, K Fragkiadaki
2023 IEEE International Conference on Robotics and Automation (ICRA), 2759-2765, 2023
1052023
Meta-rooms: Building and maintaining long term spatial models in a dynamic world
R Ambruş, N Bore, J Folkesson, P Jensfelt
2014 IEEE/RSJ international conference on intelligent robots and systems …, 2014
962014
Automatic room segmentation from unstructured 3-D data of indoor environments
R Ambruş, S Claici, A Wendt
IEEE Robotics and Automation Letters 2 (2), 749-756, 2017
952017
Multi-frame self-supervised depth with transformers
V Guizilini, R Ambruș, D Chen, S Zakharov, A Gaidon
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
932022
Sparse auxiliary networks for unified monocular depth prediction and completion
V Guizilini, R Ambrus, W Burgard, A Gaidon
Proceedings of the ieee/cvf conference on computer vision and pattern …, 2021
822021
Autonomous learning of object models on a mobile robot
T Fäulhammer, R Ambruş, C Burbridge, M Zillich, J Folkesson, N Hawes, ...
IEEE Robotics and Automation Letters 2 (1), 26-33, 2016
772016
Robust semi-supervised monocular depth estimation with reprojected distances
V Guizilini, J Li, R Ambrus, S Pillai, A Gaidon
Conference on robot learning, 503-512, 2020
702020
Shapo: Implicit representations for multi-object shape, appearance, and pose optimization
MZ Irshad, S Zakharov, R Ambrus, T Kollar, Z Kira, A Gaidon
European Conference on Computer Vision, 275-292, 2022
612022
Modeling motion patterns of dynamic objects by IOHMM
Z Wang, R Ambrus, P Jensfelt, J Folkesson
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2014
612014
Towards zero-shot scale-aware monocular depth estimation
V Guizilini, I Vasiljevic, D Chen, R Ambruș, A Gaidon
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
582023
Full surround monodepth from multiple cameras
V Guizilini, I Vasiljevic, R Ambrus, G Shakhnarovich, A Gaidon
IEEE Robotics and Automation Letters 7 (2), 5397-5404, 2022
562022
Where's waldo at time t? using spatio-temporal models for mobile robot search
T Krajník, M Kulich, L Mudrová, R Ambrus, T Duckett
2015 IEEE International Conference on Robotics and Automation (ICRA), 2140-2146, 2015
552015
Intelligent robotic perception systems
C Premebida, R Ambrus, ZC Marton
Applications of Mobile Robots, 111-127, 2018
542018
Learning optical flow, depth, and scene flow without real-world labels
V Guizilini, KH Lee, R Ambruş, A Gaidon
IEEE Robotics and Automation Letters 7 (2), 3491-3498, 2022
502022
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