Light-weight marker hiding for augmented reality. - Otto Korkalo; Miika Aittala; Sanni Siltanen (ISMAR, 2010)

Inverse lighting and photorealistic rendering for augmented reality. - Miika Aittala (Vis. Comput., 2010)

CAVE for collaborative patient room design: analysis with end-user opinion contrasting method. - Mikael Wahlström; Miika Aittala; Helinä Kotilainen; Tiina Yli-Karhu; Janne Porkka; Esa Nykänen (Virtual Real., 2010)

Practical SVBRDF capture in the frequency domain. - Miika Aittala; Tim Weyrich; Jaakko Lehtinen (ACM Trans. Graph., 2013)

Gradient-domain metropolis light transport. - Jaakko Lehtinen; Tero Karras; Samuli Laine; Miika Aittala; Frédo Durand; Timo Aila (ACM Trans. Graph., 2013)

Gradient-Domain Bidirectional Path Tracing. - Marco Manzi; Markus Kettunen 001; Miika Aittala; Jaakko Lehtinen; Frédo Durand; Matthias Zwicker (EGSR (EI&I), 2015)

Two-shot SVBRDF capture for stationary materials. - Miika Aittala; Tim Weyrich; Jaakko Lehtinen (ACM Trans. Graph., 2015)

Gradient-domain path tracing. - Markus Kettunen 001; Marco Manzi; Miika Aittala; Jaakko Lehtinen; Frédo Durand; Matthias Zwicker (ACM Trans. Graph., 2015)

Reflectance modeling by neural texture synthesis. - Miika Aittala; Timo Aila; Jaakko Lehtinen (ACM Trans. Graph., 2016)

Computational Methods for Capture and Reproduction of Photorealistic Surface Appearance ; Laskennallisia menetelmiä pintamateriaalien ulkonäön kaappaamiseen ja toisintamiseen. - Miika Aittala (2016)

Burst Image Deblurring Using Permutation Invariant Convolutional Neural Networks. - Miika Aittala; Frédo Durand (ECCV (8), 2018)

Noise2Noise: Learning Image Restoration without Clean Data. - Jaakko Lehtinen; Jacob Munkberg; Jon Hasselgren; Samuli Laine; Tero Karras; Miika Aittala; Timo Aila (ICML, 2018)

Single-image SVBRDF capture with a rendering-aware deep network. - Valentin Deschaintre; Miika Aittala; Frédo Durand; George Drettakis; Adrien Bousseau (ACM Trans. Graph., 2018)

Differentiable Monte Carlo ray tracing through edge sampling. - Tzu-Mao Li; Miika Aittala; Frédo Durand; Jaakko Lehtinen (ACM Trans. Graph., 2018)

A Dataset of Multi-Illumination Images in the Wild. - Lukas Murmann; Michaël Gharbi; Miika Aittala; Frédo Durand (ICCV, 2019)

Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization. - Miika Aittala; Prafull Sharma; Lukas Murmann; Adam B. Yedidia; Gregory W. Wornell; Bill Freeman; Frédo Durand (NeurIPS, 2019)

Flexible SVBRDF Capture with a Multi-Image Deep Network. - Valentin Deschaintre; Miika Aittala; Frédo Durand; George Drettakis; Adrien Bousseau (Comput. Graph. Forum, 2019)

Generating Training Data for Denoising Real RGB Images via Camera Pipeline Simulation. - Ronnachai Jaroensri; Camille Biscarrat; Miika Aittala; Frédo Durand (CoRR, 2019)

Sample-based Monte Carlo denoising using a kernel-splatting network. - Michaël Gharbi; Tzu-Mao Li; Miika Aittala; Jaakko Lehtinen; Frédo Durand (ACM Trans. Graph., 2019)

Analyzing and Improving the Image Quality of StyleGAN. - Tero Karras; Samuli Laine; Miika Aittala; Janne Hellsten; Jaakko Lehtinen; Timo Aila (CVPR, 2020)

Training Generative Adversarial Networks with Limited Data. - Tero Karras; Miika Aittala; Janne Hellsten; Samuli Laine; Jaakko Lehtinen; Timo Aila (NeurIPS, 2020)

What You Can Learn by Staring at a Blank Wall. - Prafull Sharma; Miika Aittala; Yoav Y. Schechner; Antonio Torralba 001; Gregory W. Wornell; William T. Freeman; Frédo Durand (ICCV, 2021)

Alias-Free Generative Adversarial Networks. - Tero Karras; Miika Aittala; Samuli Laine; Erik Härkönen; Janne Hellsten; Jaakko Lehtinen; Timo Aila (NeurIPS, 2021)

Appearance-Driven Automatic 3D Model Simplification. - Jon Hasselgren; Jacob Munkberg; Jaakko Lehtinen; Miika Aittala; Samuli Laine (EGSR (DL), 2021)

Video-Based Rendering of Dynamic Stationary Environments from Unsynchronized Inputs. - Theo Thonat; Yagiz Aksoy; Miika Aittala; Sylvain Paris; Frédo Durand; George Drettakis (Comput. Graph. Forum, 2021)

Generating Long Videos of Dynamic Scenes. - Tim Brooks; Janne Hellsten; Miika Aittala; Ting-Chun Wang; Timo Aila; Jaakko Lehtinen; Ming-Yu Liu 001; Alexei A. Efros; Tero Karras (NeurIPS, 2022)

Elucidating the Design Space of Diffusion-Based Generative Models. - Tero Karras; Miika Aittala; Timo Aila; Samuli Laine (NeurIPS, 2022)

eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers. - Yogesh Balaji; Seungjun Nah; Xun Huang; Arash Vahdat; Jiaming Song; Karsten Kreis; Miika Aittala; Timo Aila; Samuli Laine; Bryan Catanzaro; Tero Karras; Ming-Yu Liu 001 (CoRR, 2022)

Projection-Domain Self-Supervision for Volumetric Helical CT Reconstruction. - Onni Kosomaa; Samuli Laine; Tero Karras; Miika Aittala; Jaakko Lehtinen (CoRR, 2022)

Disentangling random and cyclic effects in time-lapse sequences. - Erik Härkönen; Miika Aittala; Tuomas Kynkäänniemi; Samuli Laine; Timo Aila; Jaakko Lehtinen (ACM Trans. Graph., 2022)

Generative Novel View Synthesis with 3D-Aware Diffusion Models. - Eric R. Chan; Koki Nagano; Matthew A. Chan 001; Alexander W. Bergman; Jeong Joon Park; Axel Levy; Miika Aittala; Shalini De Mello; Tero Karras; Gordon Wetzstein (ICCV, 2023)

The Role of ImageNet Classes in Fréchet Inception Distance. - Tuomas Kynkäänniemi; Tero Karras; Miika Aittala; Timo Aila; Jaakko Lehtinen (ICLR, 2023)

Data-driven Pixel Filter Aware MIP Maps for SVBRDFs. - Pauli Kemppinen; Miika Aittala; Jaakko Lehtinen (EGSR (ST), 2023)

A Hybrid Generator Architecture for Controllable Face Synthesis. - Dann Mensah; Nam Hee Kim; Miika Aittala; Samuli Laine; Jaakko Lehtinen (SIGGRAPH (Conference Paper Track), 2023)

Invertible Hierarchical Generative Model for Images. - Heikki Timonen; Miika Aittala; Jaakko Lehtinen (Trans. Mach. Learn. Res., 2023)

MesoGAN: Generative Neural Reflectance Shells. - Stavros Diolatzis; Jan Novák; Fabrice Rousselle; Jonathan Granskog; Miika Aittala; Ravi Ramamoorthi; George Drettakis (Comput. Graph. Forum, 2023)

Analyzing and Improving the Training Dynamics of Diffusion Models. - Tero Karras; Miika Aittala; Jaakko Lehtinen; Janne Hellsten; Timo Aila; Samuli Laine (CVPR, 2024)

Guiding a Diffusion Model with a Bad Version of Itself. - Tero Karras; Miika Aittala; Tuomas Kynkäänniemi; Jaakko Lehtinen; Timo Aila; Samuli Laine (NeurIPS, 2024)

Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models. - Tuomas Kynkäänniemi; Miika Aittala; Tero Karras; Samuli Laine; Timo Aila; Jaakko Lehtinen (NeurIPS, 2024)

Elucidated Rolling Diffusion Models for Probabilistic Weather Forecasting. - Salva Rühling Cachay; Miika Aittala; Karsten Kreis; Noah D. Brenowitz; Arash Vahdat; Morteza Mardani; Rose Yu (CoRR, 2025)