Jaakko Lehtinen
Jaakko Lehtinen
Associate Professor, Aalto University & Distinguished Research Scientist, NVIDIA
Verified email at aalto.fi - Homepage
Title
Cited by
Cited by
Year
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
38212018
Analyzing and improving the image quality of StyleGAN
T Karras, S Laine, M Aittala, J Hellsten, J Lehtinen, T Aila
Proc. Computer Vision and Pattern Recognition (CVPR), 2020
11782020
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
6382018
Few-shot unsupervised image-to-image translation
MY Liu, X Huang, A Mallya, T Karras, T Aila, J Lehtinen, J Kautz
International Conference on Computer Vision (ICCV) 2019, 2019
3092019
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 (NeurIPS 2020), 2020
2512020
Differentiable Monte Carlo Ray Tracing through Edge Sampling
TM Li, M Aittala, F Durand, J Lehtinen
ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2018) 37 (6), Article 222, 2018
2172018
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
1872017
Incremental instant radiosity for real-time indirect illumination
S Laine, H Saransaari, J Lehtinen, J Kontkanen, T Aila
Proc. Eurographics Symposium on Rendering 2007, 4-8, 2007
1722007
GANSpace: Discovering Interpretable GAN Controls
E Härkönen, A Hertzmann, J Lehtinen, S Paris
Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020
1492020
Learning to predict 3D objects with an interpolation-based differentiable renderer
W Chen, H Ling, J Gao, E Smith, J Lehtinen, A Jacobson, S Fidler
Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 9605-9616, 2019
1392019
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 (NeurIPS 2019), 2019
1332019
Recent advances in adaptive sampling and reconstruction for Monte Carlo rendering
M Zwicker, W Jarosz, J Lehtinen, B Moon, R Ramamoorthi, F Rousselle, ...
Computer Graphics Forum 34 (2), 667-681, 2015
1262015
Matrix radiance transfer
J Lehtinen, J Kautz
Proceedings of the 2003 symposium on Interactive 3D graphics, 59-64, 2003
1232003
Two-shot SVBRDF capture for stationary materials
M Aittala, T Weyrich, J Lehtinen
ACM Transactions on Graphics 34 (4), 110, 2015
1212015
High-quality self-supervised deep image denoising
S Laine, T Karras, J Lehtinen, T Aila
Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 2019
1152019
Temporal light field reconstruction for rendering distribution effects
J Lehtinen, T Aila, J Chen, S Laine, F Durand
ACM SIGGRAPH 2011 papers, 1-12, 2011
1092011
Decoupled sampling for graphics pipelines
J Ragan-Kelley, J Lehtinen, J Chen, M Doggett, F Durand
ACM Transactions on Graphics (TOG) 30 (3), 1-17, 2011
1062011
Soft shadow volumes for ray tracing
S Laine, T Aila, U Assarsson, J Lehtinen, T Akenine-Möller
ACM SIGGRAPH 2005 Papers, 1156-1165, 2005
1042005
Practical SVBRDF capture in the frequency domain.
M Aittala, T Weyrich, J Lehtinen
ACM Trans. Graph. 32 (4), 110:1-110:12, 2013
1032013
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
99*2017
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Articles 1–20