Methods › Computer Vision › Generative Models › HiSD
Hierarchical Style Disentanglement
HiSD
Introduced by Xinyang Li et al. in Image-to-image Translation via Hierarchical Style Disentanglement
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Hierarchical Style Disentanglement, or HiSD, aims to disentangle different styles in image-to-image translation models. It organizes the labels into a hierarchical structure, where independent tags, exclusive attributes, and disentangled styles are allocated from top to bottom. To make the styles identified to the tags and attributes, the authors carefully redesign the modules, phases, and objectives.
Papers archive 2025-07-28
2 shown of 2, 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.
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Neural Network-based High-index Saddle Dynamics Method for Searching Saddle Points and Solution Landscape 25 Nov 2024 · 0 repositories · arXiv:2411.16200
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Image-to-image Translation via Hierarchical Style Disentanglement 2 Mar 2021 · 1 repository · arXiv:2103.01456
Tasks archive 2025-07-28
4 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Disentanglement | 1 |
| Image-to-Image Translation | 1 |
| Multimodal Unsupervised Image-To-Image Translation | 1 |
| Translation | 1 |
Usage over time archive 2025-07-28
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
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