3 papers
cs.CV2025
BizGen: Advancing Article-level Visual Text Rendering for Infographics Generation
Yuyang Peng, Shishi Xiao, Keming Wu +6
Recently, state-of-the-art text-to-image generation models, such as Flux and Ideogram 2.0, have made significant progress in sentence-level visual text rendering. In this paper, we…
cs.CV2025
PrismLayers: Open Data for High-Quality Multi-Layer Transparent Image Generative Models
Junwen Chen, Heyang Jiang, Yanbin Wang +6
Generating high-quality, multi-layer transparent images from text prompts can unlock a new level of creative control, allowing users to edit each layer as effortlessly as editing t…
cs.CV2025
Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization
Zhanhao Liang, Yuhui Yuan, Shuyang Gu +5
Generating visually appealing images is fundamental to modern text-to-image generation models. A potential solution to better aesthetics is direct preference optimization (DPO), wh…