| A style-based generator architecture for generative adversarial networks T Karras, S Laine, T Aila Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 11041 | 2019 |
| Progressive growing of gans for improved quality, stability, and variation T Karras, T Aila, S Laine, J Lehtinen arXiv preprint arXiv:1710.10196, 2017 | 8271 | 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 | 5987 | 2020 |
| Temporal ensembling for semi-supervised learning S Laine, T Aila arXiv preprint arXiv:1610.02242, 2016 | 2963 | 2016 |
| Pruning convolutional neural networks for resource efficient inference P Molchanov, S Tyree, T Karras, T Aila, J Kautz Proc. ICLR 2017, 2016 | 2639* | 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, 12104-12114, 2020 | 1828 | 2020 |
| Noise2Noise: Learning image restoration without clean data J Lehtinen, J Munkberg, J Hasselgren, S Laine, T Karras, M Aittala, T Aila arXiv preprint arXiv:1803.04189, 2018 | 1766 | 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 | 1413 | 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 | 935 | 2022 |
| Few-shot unsupervised image-to-image translation MY Liu, X Huang, A Mallya, T Karras, T Aila, J Lehtinen, J Kautz Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 825 | 2019 |
| 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 32, 2019 | 642 | 2019 |
| Understanding the efficiency of ray traversal on GPUs T Aila, S Laine Proceedings of High Performance Graphics 2009, 145-149, 2009 | 599 | 2009 |
| 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 | 505 | 2022 |
| 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 | 430 | 2017 |
| Semi-supervised semantic segmentation needs strong, varied perturbations G French, S Laine, T Aila, M Mackiewicz, G Finlayson arXiv preprint arXiv:1906.01916, 2019 | 394 | 2019 |
| Interactive reconstruction of Monte Carlo image sequences using a recurrent denoising autoencoder CRA Chaitanya, AS Kaplanyan, C Schied, M Salvi, A Lefohn, ... ACM Transactions on Graphics (TOG) 36 (4), 1-12, 2017 | 349 | 2017 |
| High-quality self-supervised deep image denoising S Laine, T Karras, J Lehtinen, T Aila Advances in Neural Information Processing Systems 32, 2019 | 336 | 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 | 310 | 2020 |
| Incremental Instant Radiosity for Real-Time Indirect Illumination. S Laine, H Saransaari, J Kontkanen, J Lehtinen, T Aila Rendering Techniques, 277-286, 2007 | 178 | 2007 |
| Fast parallel construction of high-quality bounding volume hierarchies T Karras, T Aila Proceedings of the 5th High-Performance Graphics Conference, 89-99, 2013 | 173 | 2013 |
Samuli LaineDistinguished Research Scientist, NVIDIA在 nvidia.com 的电子邮件经过验证
