arXiv:2507. 17853v2 Announce Type: replace-cross Abstract: Recent advances in text-to-image (T2I) generation have led to impressive visual results.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.
arXiv:2505. 16915v3 Announce Type: replace-cross Abstract: While recent Text-to-Image (T2I) models show impressive capabilities in synthesizing images from brief descriptions, they struggle with the long, detailed prompts required for professional applications.
arXiv:2510.12041v3 Announce Type: replace Abstract: Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models often struggle with simple or underspecifie...
CompArt introduces a new approach to aesthetic alignment in text-to-image generation by using the Principles of Art (PoA) such as Balance, Rhythm, and Emphasis to define explicit compositional constraints. The authors create a large dataset of 80,032 WikiArt images, each annotated with PoA analyses generated by a multimodal LLM, and present ArtDapter, a lightweight adapter that steers a pretrained diffusion model along ten PoA dimensions while preserving semantic fidelity. Experiments demonstrate that CompArt outperforms strong baselines in adhering to PoA controls under a dual evaluation protocol.
arXiv:2610.01723v1 Announce Type: new Abstract: Text-to-image diffusion models have achieved remarkable progress in image synthesis, yet can exhibit memorization by closely reproducing individual tra...
arXiv:2603. 28762v2 Announce Type: replace-cross Abstract: Modern Text-to-Image (T2I) diffusion models have achieved remarkable semantic alignment, yet they often suffer from a significant lack of variety, converging on a narrow set of visual solutions for any given prompt.
arXiv:2607. 26735v1 Announce Type: cross Abstract: Prompt inversion, as a typical reverse engineering technique, enables text-to-image (T2I) diffusion models to generate the desired target images without extensive prompt engineering.