11 papers · 1 filter
MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale
Zhicong Tang, Zhao Zhang, Jingye Chen +6
Layered image generation and editing is a fundamental capability that enables layer-wise reuse, editing, and composition of generated visual content, analogous to word-level editin…
Pareto-Guided Optimal Transport for Multi-Reward Alignment
Ying Ba, Tianyu Zhang, Mohan Zhou +5
Text-to-image generation models have achieved remarkable progress in preference optimization, yet achieving robust alignment across diverse reward models remains a significant chal…
Premier: Personalized Preference Modulation with Learnable User Embedding in Text-to-Image Generation
Zihao Wang, Yuxiang Wei, Xinpeng Zhou +5
Text-to-image generation has advanced rapidly, yet it still struggles to capture the nuanced user preferences. Existing approaches typically rely on multimodal large language model…
PrefGen: Multimodal Preference Learning for Preference-Conditioned Image Generation
Wenyi Mo, Tianyu Zhang, Yalong Bai +3
Preference-conditioned image generation seeks to adapt generative models to individual users, producing outputs that reflect personal aesthetic choices beyond the given textual pro…
Learning User Preferences for Image Generation Model
Wenyi Mo, Ying Ba, Tianyu Zhang +2
User preference prediction requires a comprehensive and accurate understanding of individual tastes. This includes both surface-level attributes, such as color and style, and deepe…
Enhancing Reward Models for High-quality Image Generation: Beyond Text-Image Alignment
Ying Ba, Tianyu Zhang, Yalong Bai +4
Contemporary image generation systems have achieved high fidelity and superior aesthetic quality beyond basic text-image alignment. However, existing evaluation frameworks have fai…
V2Flow: Unifying Visual Tokenization and Large Language Model Vocabularies for Autoregressive Image Generation
Guiwei Zhang, Tianyu Zhang, Mohan Zhou +2
We propose V2Flow, a novel tokenizer that produces discrete visual tokens capable of high-fidelity reconstruction, while ensuring structural and latent distribution alignment with…
Uniform Attention Maps: Boosting Image Fidelity in Reconstruction and Editing
Wenyi Mo, Tianyu Zhang, Yalong Bai +2
Text-guided image generation and editing using diffusion models have achieved remarkable advancements. Among these, tuning-free methods have gained attention for their ability to p…
STAR: Scale-wise Text-conditioned AutoRegressive image generation
Xiaoxiao Ma, Mohan Zhou, Tao Liang +5
We introduce STAR, a text-to-image model that employs a scale-wise auto-regressive paradigm. Unlike VAR, which is constrained to class-conditioned synthesis for images up to 256$\t…
Dynamic Prompt Optimizing for Text-to-Image Generation
Wenyi Mo, Tianyu Zhang, Yalong Bai +3
Text-to-image generative models, specifically those based on diffusion models like Imagen and Stable Diffusion, have made substantial advancements. Recently, there has been a surge…
StyleInject: Parameter Efficient Tuning of Text-to-Image Diffusion Models
Mohan Zhou, Yalong Bai, Qing Yang +1
The ability to fine-tune generative models for text-to-image generation tasks is crucial, particularly facing the complexity involved in accurately interpreting and visualizing tex…