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David Acuna
David Acuna
Verified email at cs.toronto.edu - Homepage
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Cited by
Cited by
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
6522018
Gated-scnn: Gated shape cnns for semantic segmentation
T Takikawa, D Acuna, V Jampani, S Fidler
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
4762019
Efficient interactive annotation of segmentation datasets with polygon-rnn++
D Acuna, H Ling, A Kar, S Fidler
Proceedings of the IEEE conference on Computer Vision and Pattern …, 2018
3372018
Meta-sim: Learning to generate synthetic datasets
A Kar, A Prakash, MY Liu, E Cameracci, J Yuan, M Rusiniak, D Acuna, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
1632019
Devil is in the edges: Learning semantic boundaries from noisy annotations
D Acuna, A Kar, S Fidler
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
1382019
Structured domain randomization: Bridging the reality gap by context-aware synthetic data
A Prakash, S Boochoon, M Brophy, D Acuna, E Cameracci, G State, ...
2019 International Conference on Robotics and Automation (ICRA), 7249-7255, 2019
1332019
Object instance annotation with deep extreme level set evolution
Z Wang, D Acuna, H Ling, A Kar, S Fidler
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
632019
Neural turtle graphics for modeling city road layouts
H Chu, D Li, D Acuna, A Kar, M Shugrina, X Wei, MY Liu, A Torralba, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
452019
State, G., Shapira, O., Birchfield, S.: Structured domain randomization: Bridging the reality gap by context-aware synthetic data
A Prakash, S Boochoon, M Brophy, D Acuna, E Cameracci
Proceedings of the IEEE, 2019
402019
Neural data server: A large-scale search engine for transfer learning data
X Yan, D Acuna, S Fidler
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020
282020
f-domain adversarial learning: Theory and algorithms
D Acuna, G Zhang, MT Law, S Fidler
International Conference on Machine Learning, 66-75, 2021
252021
Variational amodal object completion
H Ling, D Acuna, K Kreis, SW Kim, S Fidler
Advances in Neural Information Processing Systems 33, 16246-16257, 2020
182020
Towards real-time detection and tracking of basketball players using deep neural networks
D Acuna
Proceedings of the 31st Conference on Neural Information Processing Systems …, 2017
172017
Generation of synthetic images for training a neural network model
J Tremblay, A Prakash, MA Brophy, V Jampani, C Anil, ST Birchfield, ...
US Patent 10,867,214, 2020
112020
Gated-scnn: Gated shape CNNs for semantic segmentation. arXiv 2019
T Takikawa, D Acuna, V Jampani, S Fidler
arXiv preprint arXiv:1907.05740, 0
10
Learning to generate synthetic datasets for traning neural networks
A Kar, A Prakash, MY Liu, DJA Marrero, AT Barriuso, S Fidler
US Patent App. 16/685,795, 2020
72020
Systems and methods for polygon object annotation and a method of training and object annotation system
S Fidler, A Kar, H Ling, J Gao, W Chen, DJA Marrero
US Patent 10,643,130, 2020
52020
Unsupervised modeling of the movement of basketball players using a deep generative model
D Acuna
52020
Complex Momentum for Optimization in Games
JP Lorraine, D Acuna, P Vicol, D Duvenaud
International Conference on Artificial Intelligence and Statistics, 7742-7765, 2022
32022
Domain Adversarial Training: A Game Perspective
D Acuna, MT Law, G Zhang, S Fidler
arXiv preprint arXiv:2202.05352, 2022
32022
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