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Samuli Laine
Samuli Laine
Distinguished Research Scientist, NVIDIA
Verified email at nvidia.com - Homepage
Title
Cited by
Cited by
Year
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
132412018
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
94252017
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
72562020
Temporal ensembling for semi-supervised learning
S Laine, T Aila
International Conference on Learning Representations (ICLR) 2017, 2016
33432016
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
22052020
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
20632018
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
17872021
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
15822022
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
8352019
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
7252022
Understanding the efficiency of ray traversal on GPUs
T Aila, S Laine
Proceedings of High Performance Graphics 2009, 145-149, 2009
6192009
Semi-supervised semantic segmentation needs strong, varied perturbations
G French, S Laine, T Aila, M Mackiewicz, G Finlayson
520*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
4922017
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
4322020
Efficient sparse voxel octrees
S Laine, T Karras
IEEE Transactions on Visualization and Computer Graphics 17 (8), 1048-1059, 2011
4162011
High-quality self-supervised deep image denoising
S Laine, T Karras, J Lehtinen, T Aila
Advances in Neural Information Processing Systems, 6970-6980, 2019
4042019
Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis
A Sauer, T Karras, S Laine, A Geiger, T Aila
International conference on machine learning, 30105-30118, 2023
2282023
Ambient occlusion fields
J Kontkanen, S Laine
Proceedings of the 2005 symposium on Interactive 3D graphics and games, 41-48, 2005
1952005
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
1822007
Megakernels considered harmful: wavefront path tracing on GPUs
S Laine, T Karras, T Aila
Proceedings of High Performance Graphics 2013, 137-143, 2013
1512013
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