| Analyzing and improving the image quality of stylegan T Karras, S Laine, M Aittala, J Hellsten, J Lehtinen, T Aila Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 6091 | 2020 |
| Training generative adversarial networks with limited data T Karras, M Aittala, J Hellsten, S Laine, J Lehtinen, T Aila Advances in neural information processing systems 33, 12104-12114, 2020 | 1861 | 2020 |
| Alias-free generative adversarial networks T Karras, M Aittala, S Laine, E Härkönen, J Hellsten, J Lehtinen, T Aila Advances in neural information processing systems 34, 852-863, 2021 | 1444 | 2021 |
| Modular primitives for high-performance differentiable rendering S Laine, J Hellsten, T Karras, Y Seol, J Lehtinen, T Aila ACM Transactions on Graphics (ToG) 39 (6), 1-14, 2020 | 321 | 2020 |
| Generating long videos of dynamic scenes T Brooks, J Hellsten, M Aittala, TC Wang, T Aila, J Lehtinen, MY Liu, ... Advances in Neural Information Processing Systems 35, 31769-31781, 2022 | 78 | 2022 |
| Analyzing and improving the training dynamics of diffusion models T Karras, M Aittala, J Lehtinen, J Hellsten, T Aila, S Laine Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 22 | 2024 |
| Analyzing and improving the image quality of styleGAN. IEEE T Karras, S Laine, M Aittala, J Hellsten, J Lehtinen, T Aila CVF Conference on Computer Vision and Pattern Recognition (CVPR), 0 | 3 | |
| User Interfaces and Methods for Generating a New Artifact Based on Existing Artifacts J Hellsten, TT Karras, SM Laine US Patent App. 17/344,053, 2022 | 2 | 2022 |
| Training neural networks with limited data using invertible augmentation operators TT Karras, MS Aittala, JJ Hellsten, SM Laine, JT Lehtinen, TO Aila US Patent App. 17/210,934, 2021 | 2 | 2021 |
| Weight demodulation for a generative neural network TT Karras, SM Laine, JT Lehtinen, MS Aittala, JJ Hellsten, TO Aila US Patent 11,605,001, 2023 | 1 | 2023 |
| Image-space painterly rendering J Hellstn | 1 | 2008 |
| User interfaces and methods for generating a new artifact based on existing artifacts J Hellsten, TT Karras, SM Laine US Patent 11,921,997, 2024 | | 2024 |
| Three-dimensional model recovery from two-dimensional images SM Laine, JJ Hellsten, TT Karras, S Yeongho, JT Lehtinen, TO Aila US Patent 11,734,890, 2023 | | 2023 |
| Smoothing regularization for a generative neural network TT Karras, SM Laine, JT Lehtinen, MS Aittala, JJ Hellsten, TO Aila US Patent 11,620,521, 2023 | | 2023 |
| Fused processing of a continuous mathematical operator TT Karras, MS Aittala, SM Laine, EA Härkönen, JJ Hellsten, JT Lehtinen, ... US Patent App. 17/562,521, 2022 | | 2022 |
| Generative neural networks with reduced aliasing TT Karras, MS Aittala, SM Laine, EA Härkönen, JJ Hellsten, JT Lehtinen, ... US Patent App. 17/562,494, 2022 | | 2022 |
| User interfaces and methods for generating a new artifact based on existing artifacts J Hellsten, TT Karras, SM Laine US Patent 11,435,885, 2022 | | 2022 |
| Progressive modification of neural networks TT Karras, TO Aila, SM Laine, JT Lehtinen, J Hellsten US Patent 11,263,525, 2022 | | 2022 |
| Bardes, A., Ponce, J., & LeCun, Y. Vicreg: Variance-invariance-covariance regularization for self-supervised learning. arXiv preprint arXiv: 2105.04906, 2021. T Karras, S Laine, M Aittala, J Hellsten, J Lehtinen, T Aila | | |
| Supplemental Material: Analyzing and Improving the Image Quality of StyleGAN T Karras, S Laine, M Aittala, J Hellsten, J Lehtinen, T Aila | | |
