Miika Aittala

6.1k total citations · 1 hit paper
23 papers, 1.4k citations indexed

About

Miika Aittala is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics. According to data from OpenAlex, Miika Aittala has authored 23 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 14 papers in Computer Graphics and Computer-Aided Design and 6 papers in Computational Mechanics. Recurrent topics in Miika Aittala's work include Advanced Vision and Imaging (14 papers), Computer Graphics and Visualization Techniques (14 papers) and Generative Adversarial Networks and Image Synthesis (7 papers). Miika Aittala is often cited by papers focused on Advanced Vision and Imaging (14 papers), Computer Graphics and Visualization Techniques (14 papers) and Generative Adversarial Networks and Image Synthesis (7 papers). Miika Aittala collaborates with scholars based in Finland, United States and United Kingdom. Miika Aittala's co-authors include Jaakko Lehtinen, Frédo Durand, Timo Aila, Tzu‐Mao Li, Tim Weyrich, Tero Karras, Samuli Laine, George Drettakis, Valentin Deschaintre and Jacob Munkberg and has published in prestigious journals such as ACM Transactions on Graphics, Computer Graphics Forum and The Visual Computer.

In The Last Decade

Miika Aittala

23 papers receiving 1.3k citations

Hit Papers

Differentiable Monte Carl... 2018 2026 2020 2023 2018 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Differentiable Monte Carlo ray tracing through edge sampling
    2018 259 citations Tzu‐Mao Li, Miika Aittala et al. ACM Transactions on Graphics profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Miika Aittala 1.1k 770 353 100 84 23 1.4k
Yue Dong 1.0k 1.0× 872 1.1× 436 1.2× 69 0.7× 109 1.3× 39 1.3k
Morgan McGuire 946 0.9× 749 1.0× 310 0.9× 160 1.6× 51 0.6× 48 1.4k
Yoshinori Dobashi 1.0k 1.0× 1.3k 1.7× 691 2.0× 94 0.9× 35 0.4× 139 1.7k
Nicolas Holzschuch 1.0k 1.0× 977 1.3× 504 1.4× 130 1.3× 38 0.5× 55 1.3k
Stephen Lombardi 1.5k 1.4× 734 1.0× 701 2.0× 201 2.0× 28 0.3× 22 1.8k
Jon Hasselgren 752 0.7× 511 0.7× 274 0.8× 121 1.2× 64 0.8× 42 1.0k
Toshiya Hachisuka 1.0k 1.0× 1.1k 1.4× 385 1.1× 70 0.7× 139 1.7× 58 1.5k
Jacob Munkberg 691 0.7× 504 0.7× 287 0.8× 99 1.0× 67 0.8× 39 925
Kadi Bouatouch 896 0.8× 700 0.9× 335 0.9× 59 0.6× 32 0.4× 113 1.2k
Zhengqin Li 897 0.8× 340 0.4× 196 0.6× 234 2.3× 34 0.4× 24 1.2k

Countries citing papers authored by Miika Aittala

Since Specialization
Citations

This map shows the geographic impact of Miika Aittala's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Miika Aittala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Miika Aittala more than expected).

Fields of papers citing papers by Miika Aittala

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Miika Aittala. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Miika Aittala. The network helps show where Miika Aittala may publish in the future.

Co-authorship network of co-authors of Miika Aittala

This figure shows the co-authorship network connecting the top 25 collaborators of Miika Aittala. A scholar is included among the top collaborators of Miika Aittala based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Miika Aittala. Miika Aittala is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Karras, Tero, Miika Aittala, Jaakko Lehtinen, et al.. (2024). Analyzing and Improving the Training Dynamics of Diffusion Models. 24174–24184. 19 indexed citations
2.
Aila, Timo, Miika Aittala, Tero Karras, et al.. (2024). Guiding a Diffusion Model with a Bad Version of Itself. 52996–53021. 1 indexed citations
3.
Novák, Jan, Fabrice Rousselle, Jonathan Granskog, et al.. (2023). MesoGAN: Generative Neural Reflectance Shells. Computer Graphics Forum. 42(6). 3 indexed citations
4.
Aittala, Miika, et al.. (2023). A Hybrid Generator Architecture for Controllable Face Synthesis. Aaltodoc (Aalto University). 1–10. 2 indexed citations
5.
Chan, Eric R., Koki Nagano, Matthew A. Chan, et al.. (2023). Generative Novel View Synthesis with 3D-Aware Diffusion Models. 4194–4206. 66 indexed citations
6.
Härkönen, Erik, Miika Aittala, Tuomas Kynkäänniemi, et al.. (2022). Disentangling random and cyclic effects in time-lapse sequences. ACM Transactions on Graphics. 41(4). 1–13. 3 indexed citations
7.
Aksoy, Yağız, et al.. (2021). Video‐Based Rendering of Dynamic Stationary Environments from Unsynchronized Inputs. Computer Graphics Forum. 40(4). 73–86. 1 indexed citations
8.
Karras, Tero, Miika Aittala, Janne Hellsten, et al.. (2020). Training Generative Adversarial Networks with Limited Data. Neural Information Processing Systems. 33. 12104–12114. 40 indexed citations
9.
Aittala, Miika, et al.. (2019). Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization. arXiv (Cornell University). 32. 14311–14321. 6 indexed citations
10.
Lehtinen, Jaakko, Jacob Munkberg, Jon Hasselgren, et al.. (2018). Noise2Noise: Learning image restoration without clean data. Aaltodoc (Aalto University). 4620–4631. 208 indexed citations
11.
Li, Tzu‐Mao, Miika Aittala, Frédo Durand, & Jaakko Lehtinen. (2018). Differentiable Monte Carlo ray tracing through edge sampling. ACM Transactions on Graphics. 37(6). 1–11. 259 indexed citations breakdown →
12.
Deschaintre, Valentin, Miika Aittala, Frédo Durand, George Drettakis, & Adrien Bousseau. (2018). Single-image SVBRDF capture with a rendering-aware deep network. ACM Transactions on Graphics. 37(4). 1–15. 156 indexed citations
13.
Aittala, Miika, Timo Aila, & Jaakko Lehtinen. (2016). Reflectance modeling by neural texture synthesis. ACM Transactions on Graphics. 35(4). 1–13. 104 indexed citations
14.
Kettunen, Markus, et al.. (2015). Gradient-domain path tracing. ACM Transactions on Graphics. 34(4). 1–13. 70 indexed citations
15.
Aittala, Miika, Tim Weyrich, & Jaakko Lehtinen. (2015). Two-shot SVBRDF capture for stationary materials. ACM Transactions on Graphics. 34(4). 1–13. 101 indexed citations
16.
Kettunen, Markus, et al.. (2015). Gradient-Domain Bidirectional Path Tracing. Eurographics. 15 indexed citations
17.
Lehtinen, Jaakko, Tero Karras, Samuli Laine, et al.. (2013). Gradient-domain metropolis light transport. ACM Transactions on Graphics. 32(4). 1–12. 68 indexed citations
18.
Aittala, Miika, et al.. (2010). Light-weight marker hiding for augmented reality. 247–248. 21 indexed citations
19.
Aittala, Miika. (2010). Inverse lighting and photorealistic rendering for augmented reality. The Visual Computer. 26(6-8). 669–678. 43 indexed citations
20.
Wahlström, Mikael, et al.. (2009). CAVE for collaborative patient room design: analysis with end-user opinion contrasting method. Virtual Reality. 14(3). 197–211. 16 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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