| A style-based generator architecture for generative adversarial networks T Karras, S Laine, T Aila IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019, 2018 | 10390 | 2018 |
| Progressive growing of gans for improved quality, stability, and variation T Karras, T Aila, S Laine, J Lehtinen International Conference on Learning Representations (ICLR) 2018, 2017 | 7966 | 2017 |
| 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 | 5617 | 2020 |
| Temporal ensembling for semi-supervised learning S Laine, T Aila International Conference on Learning Representations (ICLR) 2017, 2016 | 2818 | 2016 |
| 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, 2020 | 1718 | 2020 |
| Noise2noise: Learning image restoration without clean data J Lehtinen, J Munkberg, J Hasselgren, S Laine, T Karras, M Aittala, T Aila International Conference on Machine Learning (ICML) 2018, 2018 | 1668 | 2018 |
| 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 | 1292 | 2021 |
| Elucidating the design space of diffusion-based generative models T Karras, M Aittala, T Aila, S Laine Advances in Neural Information Processing Systems 35, 26565-26577, 2022 | 745 | 2022 |
| Understanding the efficiency of ray traversal on GPUs T Aila, S Laine Proceedings of High Performance Graphics 2009, 145-149, 2009 | 594 | 2009 |
| Improved precision and recall metric for assessing generative models T Kynkäänniemi, T Karras, S Laine, J Lehtinen, T Aila Advances in Neural Information Processing Systems, 3927-3936, 2019 | 570 | 2019 |
| ediff-i: Text-to-image diffusion models with an ensemble of expert denoisers Y Balaji, S Nah, X Huang, A Vahdat, J Song, Q Zhang, K Kreis, M Aittala, ... arXiv preprint arXiv:2211.01324, 2022 | 419 | 2022 |
| Semi-supervised semantic segmentation needs strong, varied perturbations G French, S Laine, T Aila, M Mackiewicz, G Finlayson | 415* | 2019 |
| Audio-driven facial animation by joint end-to-end learning of pose and emotion T Karras, T Aila, S Laine, A Herva, J Lehtinen ACM Transactions on Graphics (TOG) 36 (4), 1-12, 2017 | 408 | 2017 |
| Efficient sparse voxel octrees S Laine, T Karras IEEE Transactions on Visualization and Computer Graphics 17 (8), 1048-1059, 2011 | 386 | 2011 |
| High-quality self-supervised deep image denoising S Laine, T Karras, J Lehtinen, T Aila Advances in Neural Information Processing Systems, 6970-6980, 2019 | 327 | 2019 |
| 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 | 266 | 2020 |
| Ambient occlusion fields J Kontkanen, S Laine Proceedings of the 2005 symposium on Interactive 3D graphics and games, 41-48, 2005 | 193 | 2005 |
| Incremental instant radiosity for real-time indirect illumination S Laine, H Saransaari, J Kontkanen, J Lehtinen, T Aila Proceedings of Eurographics Symposium on Rendering 2007, 277-286, 2007 | 177 | 2007 |
| Alias-free shadow maps T Aila, S Laine Proceedings of Eurographics Symposium on Rendering 2004, 161-166, 2004 | 151 | 2004 |
| Megakernels considered harmful: wavefront path tracing on GPUs S Laine, T Karras, T Aila Proceedings of High Performance Graphics 2013, 137-143, 2013 | 134 | 2013 |
Timo AilaSenior Distinguished Research Scientist, NVIDIA在 nvidia.com 的電子郵件地址已通過驗證
