Methods › Computer Vision › Image Generation Models › Blended Diffusion

Blended Diffusion

3 papers tagged archive 2025-07-28

Introduced by Omri Avrahami et al. in Blended Diffusion for Text-driven Editing of Natural Images

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

Blended Diffusion enables a zero-shot local text-guided image editing of natural images. Given an input image x, an input mask m and a target guiding text t - the method enables to change the masked area within the image corresponding the the guiding text s.t. the unmasked area is left unchanged.

PaperSourceSee Code · omriav/blended-diffusion

Papers archive 2025-07-28

3 shown of 3, 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

8 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 Generation2
Image Inpainting2
Text-to-Image Generation2
Zero-Shot Text-to-Image Generation2
text-guided-image-editing2
Super-Resolution1
Vocal Bursts Intensity Prediction1
spatial-aware image editing1

Usage over time archive 2025-07-28

Papers per year tagged with Blended Diffusion: 2021 to 2022, peak 2 2 0 2021: 1 paper 2021 2022: 2 papers 2022
Papers per year the archive tags with this method, by the paper's archive date (3 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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