Methods › Computer Vision › Style Transfer Modules › Revision Network

Revision Network

4 papers tagged archive 2025-07-28

Introduced by Tianwei Lin et al. in Drafting and Revision: Laplacian Pyramid Network for Fast High-Quality Artistic Style Transfer

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

Revision Network is a style transfer module that aims to revise the rough stylized image via generating residual details image r_(c s), while the final stylized image is generated by combining r_(c s) and rough stylized image x̅_(c s). This procedure ensures that the distribution of global style pattern in x̅_(c s) is properly kept. Meanwhile, learning to revise local style patterns with residual details image is easier for the Revision Network.

As shown in the Figure, the Revision Network is designed as a simple yet effective encoder-decoder architecture, with only one down-sampling and one up-sampling layer. Further, a patch discriminator is used to help Revision Network to capture fine patch textures under adversarial learning setting. The patch discriminator D is defined following SinGAN, where D owns 5 convolution layers and 32 hidden channels. A relatively shallow D is chosen to (1) avoid overfitting since we only have one style image and (2) control the receptive field to ensure D can only capture local patterns.

PaperSource

Papers archive 2025-07-28

4 shown of 4, 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

6 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
Style Transfer2
Attribute1
Classification1
Decoder1
Object1
Zero-Shot Learning1

Usage over time archive 2025-07-28

Papers per year tagged with Revision Network: 2021 to 2024, peak 1 1 0 2021: 1 paper 2021 2022: 1 paper 2022 2023: 1 paper 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (4 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

Style Transfer Modules

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