DreamPoster fine-tunes Seedream3.0 with a deconstruction-recaptioning dataset pipeline and a three-stage curriculum to turn image-plus-text inputs into finished posters, reporting substantially higher usability than GPT-4o and SeedEdit3.0.
Postermaker: Towards high-quality product poster generation with accurate text rendering
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
DreamPoster: A Unified Framework for Image-Conditioned Generative Poster Design
DreamPoster fine-tunes Seedream3.0 with a deconstruction-recaptioning dataset pipeline and a three-stage curriculum to turn image-plus-text inputs into finished posters, reporting substantially higher usability than GPT-4o and SeedEdit3.0.