Methods › Computer Vision › Image Models › DeepSIM
DeepSIM
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
DeepSIM is a generative model for conditional image manipulation based on a single image. The network learns to map between a primitive representation of the image to the image itself. At manipulation time, the generator allows for making complex image changes by modifying the primitive input representation and mapping it through the network. The choice of a primitive representations has an impact on the ease and expressiveness of the manipulations and can be automatic (e.g. edges), manual, or hybrid such as edges on top of segmentations.
Papers archive 2025-07-28
1 shown of 1, 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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Image Shape Manipulation from a Single Augmented Training Sample 13 Sep 2021 · 1 repository · arXiv:2109.06151
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 |
|---|---|
| Image Generation | 1 |
| Image Manipulation | 1 |
| Image-to-Image Translation | 1 |
| Sketch-to-Image 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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections