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Adaptive Instance Normalization

429 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Adaptive Instance Normalization is a normalization method that aligns the mean and variance of the content features with those of the style features.

Instance Normalization normalizes the input to a single style specified by the affine parameters. Adaptive Instance Normaliation is an extension. In AdaIN, we receive a content input x and a style input y, and we simply align the channel-wise mean and variance of x to match those of y. Unlike Batch Normalization, Instance Normalization or Conditional Instance Normalization, AdaIN has no learnable affine parameters. Instead, it adaptively computes the affine parameters from the style input:

AdaIN(x, y)= σ(y)((x-μ(x))/(σ(x)))+μ(y)

Source: Arbitrary Style Transfer in Real-time with Adaptive...See Code · naoto0804/pytorch-AdaIN

Papers archive 2025-07-28

30 shown of 429, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 229 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Image Generation88
Attribute45
Disentanglement42
Style Transfer33
Image-to-Image Translation24
Image Manipulation22
Face Generation21
Decoder18
Face Recognition18
Generative Adversarial Network18
Translation17
Diversity16
Domain Adaptation16
Data Augmentation15
Face Swapping15
Transfer Learning13
Super-Resolution12
Semantic Segmentation11
Video Generation10
Denoising9

Usage over time archive 2025-07-28

Papers per year tagged with Adaptive Instance Normalization: 2017 to 2025, peak 106 106 0 2017: 2 papers 2017 2018: 3 papers 2018 2019: 17 papers 2019 2020: 52 papers 2020 2021: 79 papers 2021 2022: 95 papers 2022 2023: 106 papers 2023 2024: 64 papers 2024 2025: 11 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (429 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Normalization

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