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Jonathan Tremblay
Jonathan Tremblay
Verified email at nvidia.com - Homepage
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Year
Training deep networks with synthetic data: Bridging the reality gap by domain randomization
J Tremblay, A Prakash, D Acuna, M Brophy, V Jampani, C Anil, T To, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2018
5752018
Deep object pose estimation for semantic robotic grasping of household objects
J Tremblay, T To, B Sundaralingam, Y Xiang, D Fox, S Birchfield
arXiv preprint arXiv:1809.10790, 2018
4192018
Pamtri: Pose-aware multi-task learning for vehicle re-identification using highly randomized synthetic data
Z Tang, M Naphade, S Birchfield, J Tremblay, W Hodge, R Kumar, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision, 211-220, 2019
1212019
Falling things: A synthetic dataset for 3d object detection and pose estimation
J Tremblay, T To, S Birchfield
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
1162018
Synthetically trained neural networks for learning human-readable plans from real-world demonstrations
J Tremblay, T To, A Molchanov, S Tyree, J Kautz, S Birchfield
2018 IEEE International Conference on Robotics and Automation (ICRA), 5659-5666, 2018
432018
An exploration tool for predicting stealthy behaviour
J Tremblay, PA Torres, N Rikovitch, C Verbrugge
Ninth Artificial Intelligence and Interactive Digital Entertainment Conference, 2013
402013
NDDS: NVIDIA deep learning dataset synthesizer
T To, J Tremblay, D McKay, Y Yamaguchi, K Leung, A Balanon, J Cheng, ...
CVPR 2018 Workshop on Real World Challenges and New Benchmarks for Deep …, 2018
372018
Efficient geometry-aware 3D generative adversarial networks
ER Chan, CZ Lin, MA Chan, K Nagano, B Pan, S De Mello, O Gallo, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
362022
Guided uncertainty-aware policy optimization: Combining learning and model-based strategies for sample-efficient policy learning
MA Lee, C Florensa, J Tremblay, N Ratliff, A Garg, F Ramos, D Fox
2020 IEEE International Conference on Robotics and Automation (ICRA), 7505-7512, 2020
362020
Camera-to-robot pose estimation from a single image
TE Lee, J Tremblay, T To, J Cheng, T Mosier, O Kroemer, D Fox, ...
2020 IEEE International Conference on Robotics and Automation (ICRA), 9426-9432, 2020
362020
DexYCB: A benchmark for capturing hand grasping of objects
YW Chao, W Yang, Y Xiang, P Molchanov, A Handa, J Tremblay, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
332021
NDDS: NVIDIA deep learning dataset synthesizer, 2018
T To, J Tremblay, D McKay, Y Yamaguchi, K Leung, A Balanon, J Cheng, ...
29
Measuring Risk in Stealth Games
J Tremblay, PA Torres, C Verbrugge
FDG, 2014
262014
Adaptive Game Mechanics for Learning Purposes-Making Serious Games Playable and Fun.
J Tremblay, B Bouchard, A Bouzouane
CSEDU (2), 465-470, 2010
252010
Adaptive Companions in FPS Games
J Tremblay, C Verbrugge
8th International Conference on Foundations of Digital Games (FDG), 229-236, 2013
222013
Hierarchical planning for long-horizon manipulation with geometric and symbolic scene graphs
Y Zhu, J Tremblay, S Birchfield, Y Zhu
2021 IEEE International Conference on Robotics and Automation (ICRA), 6541-6548, 2021
192021
Learning robotic tasks using one or more neural networks
J Tremblay, S Birchfield, S Tyree, T To, J Kautz, A Molchanov
US Patent App. 16/255,038, 2019
182019
Deep object pose estimation for semantic robotic grasping of household objects. arXiv 2018
J Tremblay, T To, B Sundaralingam, Y Xiang, D Fox, S Birchfield
arXiv preprint arXiv:1809.10790, 0
18
Few-shot viewpoint estimation
HY Tseng, S De Mello, J Tremblay, S Liu, S Birchfield, MH Yang, J Kautz
arXiv preprint arXiv:1905.04957, 2019
162019
Target selection for AI companions in FPS games.
J Tremblay, C Dragert, C Verbrugge
FDG, 2014
162014
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