Methods › Computer Vision › Image Generation Models › Make-A-Scene

Make-A-Scene

1 paper tagged archive 2025-07-28

Introduced by Oran Gafni et al. in Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors

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

Make-A-Scene is a text-to-image method that (i) enables a simple control mechanism complementary to text in the form of a scene, (ii) introduces elements that improve the tokenization process by employing domain-specific knowledge over key image regions (faces and salient objects), and (iii) adapts classifier-free guidance for the transformer use case.

PaperSource

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.

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.

TaskPapers
Image Generation1
Semantic Segmentation1
Text to Image Generation1
Text-to-Image Generation1

Usage over time archive 2025-07-28

Papers per year tagged with Make-A-Scene: 2022 to 2022, peak 1 1 0 2022: 1 paper 2022
Papers per year the archive tags with this method, by the paper's archive date (1 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

Image Generation Models

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