| Get3d: A generative model of high quality 3d textured shapes learned from images J Gao, T Shen, Z Wang, W Chen, K Yin, D Li, O Litany, Z Gojcic, S Fidler Advances In Neural Information Processing Systems 35, 31841-31854, 2022 | 281 | 2022 |
| Editgan: High-precision semantic image editing H Ling, K Kreis, D Li, SW Kim, A Torralba, S Fidler Advances in Neural Information Processing Systems 34, 16331-16345, 2021 | 181 | 2021 |
| Semantic segmentation with generative models: Semi-supervised learning and strong out-of-domain generalization D Li, J Yang, K Kreis, A Torralba, S Fidler Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 153 | 2021 |
| 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 | 78 | 2019 |
| Bigdatasetgan: Synthesizing imagenet with pixel-wise annotations D Li, H Ling, SW Kim, K Kreis, S Fidler, A Torralba Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 62 | 2022 |
| Federated simulation for medical imaging D Li, A Kar, N Ravikumar, AF Frangi, S Fidler Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 40* | 2020 |
| Neuralfield-ldm: Scene generation with hierarchical latent diffusion models SW Kim, B Brown, K Yin, K Kreis, K Schwarz, D Li, R Rombach, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 29 | 2023 |
| A face-to-face neural conversation model H Chu, D Li, S Fidler Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 24 | 2018 |
| 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 | 17 | 2022 |
| Iterative spatial graph generation H Chu, D Li, DJA Marrero, A Kar, M Shugrina, MY Liu, AT Barriuso, ... US Patent App. 16/825,199, 2020 | 8 | 2020 |
| High-precision semantic image editing using neural networks for synthetic data generation systems and applications H Ling, K Kreis, D Li, SW Kim, AT Barriuso, S Fidler US Patent App. 17/827,394, 2022 | 5 | 2022 |
| Polymorphic-gan: Generating aligned samples across multiple domains with learned morph maps SW Kim, K Kreis, D Li, A Torralba, S Fidler Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 5 | 2022 |
| Playground v2 D Li, A Kamko, A Sabet, E Akhgari, L Xu, S Doshi https://huggingface.co/playgroundai/playground-v2-1024px-aesthetic, 2023 | 3* | 2023 |
| 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 | 3 | 2023 |
| Labeling images using a neural network D Li, S Fidler US Patent App. 17/019,120, 2022 | 2 | 2022 |
| Playground v2. 5: Three Insights towards Enhancing Aesthetic Quality in Text-to-Image Generation D Li, A Kamko, E Akhgari, A Sabet, L Xu, S Doshi arXiv preprint arXiv:2402.17245, 2024 | 1 | 2024 |
| Generating mask information D Li, H Ling, SW Kim, KJ Kreis, S Fidler, AT Barriuso US Patent App. 17/832,400, 2024 | | 2024 |
| Generating textured meshes using one or more neural networks J Gao, T Shen, Z Gojcic, W Chen, Z Wang, D Li, O Litany, S Fidler US Patent App. 17/895,793, 2024 | | 2024 |
| RadImageGAN--A Multi-modal Dataset-Scale Generative AI for Medical Imaging Z Liu, A Zhou, A Yang, A Yilmaz, M Yoo, M Sullivan, C Zhang, J Grant, ... arXiv preprint arXiv:2312.05953, 2023 | | 2023 |
| Estimating optimal training data set size for machine learning model systems and applications RR Mahmood, JR Lucas, DJA Marrero, D Li, J Philion, JMA Lopez, Z Yu, ... US Patent App. 17/828,663, 2023 | | 2023 |
Sanja FidlerUniversity of Toronto, NVIDIADirección de correo verificada de cs.toronto.edu
