Samuli Laine

NVIDIA

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His research interests have ranged from photorealistic and real-time rendering to voxel-based graphics, GPU ray tracing, and 3D content creation. Currently Dr. Laine focuses on deep learning and its applications in computer graphics.

Papers74 papers

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Training Generative Adversarial Networks with Limited Data

Karras Tero,Aittala Miika,Hellsten Janne,Laine Samuli,Lehtinen Jaakko,Aila Timo

NeurIPS, (2020)

Cited by5EIBibtex

Modular Primitives for High-Performance Differentiable Rendering

Samuli Laine, Janne Hellsten,Tero Karras, Yeongho Seol,Jaakko Lehtinen,Timo Aila

ACM Trans. Graph., no. 6 (2020): 1-14

EIBibtex

A Style-Based Generator Architecture for Generative Adversarial Networks

Tero Karras,Samuli Laine,Timo Aila

IEEE transactions on pattern analysis and machine intelligence, (2020): 1-1

Cited by1246WOSEIBibtex

Self-Supervised Deep Image Denoising

Samuli Laine,Jaakko Lehtinen,Timo Aila

arXiv: Learning, (2019)

EIBibtex

High-Quality Self-Supervised Deep Image Denoising

Samuli Laine,Tero Karras,Jaakko Lehtinen,Timo Aila

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), (2019): 6968-6978

Cited by31EIBibtex

Consistency regularization and CutMix for semi-supervised semantic segmentation

Geoffrey French,Timo Aila,Samuli Laine,Michal Mackiewicz,Graham D. Finlayson

CoRR, (2019)

Cited by3EIBibtex

Improved Precision and Recall Metric for Assessing Generative Models

Tuomas Kynkäänniemi,Tero Karras,Samuli Laine,Jaakko Lehtinen,Timo Aila

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), (2019): 3929-3938

Cited by38EIBibtex

Analyzing and Improving the Image Quality of StyleGAN

Karras Tero,Laine Samuli,Aittala Miika,Hellsten Janne,Lehtinen Jaakko,Aila Timo

CVPR, pp.8107-8116, (2019)

Cited by196EIBibtex

NVGaze - An Anatomically-Informed Dataset for Low-Latency, Near-Eye Gaze Estimation

Joohwan Kim,Michael Stengel, Alexander Majercik,Shalini De Mello, David Dunn,Samuli Laine,Morgan McGuire,David Luebke

CHI, pp.550, (2019)

Cited by18EIBibtex

Noise2Noise: Learning Image Restoration without Clean Data

Jaakko Lehtinen,Jacob Munkberg,Jon Hasselgren,Samuli Laine,Tero Karras,Miika Aittala,Timo Aila

ICML, (2018): 4620-4631

Cited by299EIBibtex

Feature-Based Metrics for Exploring the Latent Space of Generative Models

Samuli Laine

ICLR, (2018)

EIBibtex

Progressive Growing of GANs for Improved Quality, Stability, and Variation

Tero Karras,Timo Aila,Samuli Laine,Jaakko Lehtinen

international conference on learning representations, (2018)

Cited by2254EIBibtex

Noise2Noise: Learning Image Restoration without Clean Training Images

Samuli Laine,Timo Aila,Jaakko Lehtinen,Jaakko Lehtinen,Tero Karras,Jacob Munkberg, Jon N. Hasselgren,Miika Aittala

international conference on machine learning, (2018)

Bibtex

Temporal Ensembling for Semi-Supervised Learning

Samuli Laine,Timo Aila

ICLR, (2017)

Cited by4EIBibtex

Audio-driven facial animation by joint end-to-end learning of pose and emotion

Tero Karras,Timo Aila,Samuli Laine, Antti Herva,Jaakko Lehtinen

ACM Trans. Graph., no. 4 (2017)

Cited by128EIBibtex

Efficient incoherent ray traversal on GPUs through compressed wide BVHs

Henri Ylitie,Tero Karras,Samuli Laine

High Performance Graphics, (2017)

Cited by26EIBibtex

Production-level facial performance capture using deep convolutional neural networks

Samuli Laine,Tero Karras,Timo Aila, Antti Herva,Shunsuke Saito, Ronald Yu,Hao Li,Jaakko Lehtinen

Symposium on Computer Animation, (2017)

Cited by66EIBibtex

Facial Performance Capture with Deep Neural Networks

Samuli Laine,Tero Karras,Timo Aila, Antti Herva,Jaakko Lehtinen

arXiv: Computer Vision and Pattern Recognition, (2016)

Cited by7EIBibtex

System and method for estimating signal-dependent noise of an image

Timo Aila,Samuli Laine

(2015)

Bibtex

Apex Point Map for Constant-Time Bounding Plane Approximation

Samuli Laine,Tero Karras

EGSR, pp.51-55, (2015)

Cited by1EIBibtex

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