collaborators

5 papers

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

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.CV2024

Efficient Diffusion Transformer with Step-wise Dynamic Attention Mediators

Yifan Pu, Zhuofan Xia, Jiayi Guo +9

This paper identifies significant redundancy in the query-key interactions within self-attention mechanisms of diffusion transformer models, particularly during the early stages of…

cs.CV2024

FontStudio: Shape-Adaptive Diffusion Model for Coherent and Consistent Font Effect Generation

Xinzhi Mu, Li Chen, Bohan Chen +5

Recently, the application of modern diffusion-based text-to-image generation models for creating artistic fonts, traditionally the domain of professional designers, has garnered si…

cs.CV2024

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…