Progressive growing of gans for improved quality, stability, and variation T Karras, T Aila, S Laine, J Lehtinen arXiv preprint arXiv:1710.10196, 2017 | 2667 | 2017 |
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 | 1718 | 2019 |
Pruning convolutional neural networks for resource efficient inference P Molchanov, S Tyree, T Karras, T Aila, J Kautz arXiv preprint arXiv:1611.06440, 2016 | 742 | 2016 |
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 | 412 | 2018 |
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 | 383 | 2020 |
Efficient sparse voxel octrees S Laine, T Karras IEEE Transactions on Visualization and Computer Graphics 17 (8), 1048-1059, 2010 | 300 | 2010 |
Pruning convolutional neural networks for resource efficient transfer learning P Molchanov, S Tyree, T Karras, T Aila, J Kautz arXiv preprint arXiv:1611.06440 3, 2016 | 215 | 2016 |
Maximizing parallelism in the construction of BVHs, octrees, and k-d trees T Karras Proceedings of the Fourth ACM SIGGRAPH/Eurographics conference on High …, 2012 | 174 | 2012 |
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 | 170 | 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 | 142 | 2017 |
Fast parallel construction of high-quality bounding volume hierarchies T Karras, T Aila Proceedings of the 5th High-Performance Graphics Conference, 89-99, 2013 | 119 | 2013 |
Architecture considerations for tracing incoherent rays T Aila, T Karras Proceedings of the Conference on High Performance Graphics, 113-122, 2010 | 95 | 2010 |
Megakernels considered harmful: Wavefront path tracing on GPUs S Laine, T Karras, T Aila Proceedings of the 5th High-Performance Graphics Conference, 137-143, 2013 | 93 | 2013 |
Understanding the efficiency of ray traversal on GPUs–Kepler and Fermi addendum T Aila, S Laine, T Karras NVIDIA Corporation, NVIDIA Technical Report NVR-2012-02, 2012 | 85 | 2012 |
Production-level facial performance capture using deep convolutional neural networks S Laine, T Karras, T Aila, A Herva, S Saito, R Yu, H Li, J Lehtinen Proceedings of the ACM SIGGRAPH/Eurographics symposium on computer animation …, 2017 | 81 | 2017 |
High-performance software rasterization on GPUs S Laine, T Karras Proceedings of the ACM SIGGRAPH Symposium on High Performance Graphics, 79-88, 2011 | 71 | 2011 |
Conservative rasterization of primitives using an error term EB Lum, WR Steiner, HP Moreton, JL Cobb, BN Rodgers, Y Uralsky, ... US Patent 9,633,469, 2017 | 69 | 2017 |
Gradient-domain metropolis light transport J Lehtinen, T Karras, S Laine, M Aittala, F Durand, T Aila ACM Transactions on Graphics (TOG) 32 (4), 1-12, 2013 | 68 | 2013 |
High-quality self-supervised deep image denoising S Laine, T Karras, J Lehtinen, T Aila arXiv preprint arXiv:1901.10277, 2019 | 57 | 2019 |
Improved precision and recall metric for assessing generative models T Kynkäänniemi, T Karras, S Laine, J Lehtinen, T Aila arXiv preprint arXiv:1904.06991, 2019 | 56 | 2019 |