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David Acuna
David Acuna
Verified email at cs.toronto.edu - Homepage
Title
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
13172018
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
9422019
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
5652018
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
3422019
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
2642019
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
2152019
Gavriel State, Omer Shapira, and Stan Birchfield. Structured domain randomization: Bridging the reality gap by context-aware synthetic data
A Prakash, S Boochoon, M Brophy, D Acuna, E Cameracci
2019 International Conference on Robotics and Automation (ICRA), 7249-7255, 2019
1842019
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
1162019
f-domain adversarial learning: Theory and algorithms
D Acuna, G Zhang, MT Law, S Fidler
International Conference on Machine Learning, 66-75, 2021
1092021
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
1072019
Learning to generate synthetic datasets for training neural networks
A Kar, A Prakash, MY Liu, DJA Marrero, AT Barriuso, S Fidler
US Patent 11,610,115, 2023
652023
Variational amodal object completion
H Ling, D Acuna, K Kreis, SW Kim, S Fidler
Advances in Neural Information Processing Systems 33, 16246-16257, 2020
622020
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
612020
Neural light field estimation for street scenes with differentiable virtual object insertion
Z Wang, W Chen, D Acuna, J Kautz, S Fidler
European Conference on Computer Vision, 380-397, 2022
522022
How much more data do i need? estimating requirements for downstream tasks
R Mahmood, J Lucas, D Acuna, D Li, J Philion, JM Alvarez, Z Yu, S Fidler, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
492022
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
432020
Reasoning paths with reference objects elicit quantitative spatial reasoning in large vision-language models
YH Liao, R Mahmood, S Fidler, D Acuna
arXiv preprint arXiv:2409.09788, 2024
382024
Dreamteacher: Pretraining image backbones with deep generative models
D Li, H Ling, A Kar, D Acuna, SW Kim, K Kreis, A Torralba, S Fidler
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
342023
Federated learning with heterogeneous architectures using graph hypernetworks
O Litany, H Maron, D Acuna, J Kautz, G Chechik, S Fidler
arXiv preprint arXiv:2201.08459, 2022
332022
Object image completion
S Fidler, DA Marrero, SW Kim, KJ Kreis, H Ling
US Patent 12,475,604, 2025
302025
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