7 papers
Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models
Jiayi Guo, Linqing Wang, Jiangshan Wang +6
Unified multimodal models (UMMs) integrate visual understanding and generation within a single framework. For text-to-image (T2I) tasks, this unified capability allows UMMs to refi…
Meta-CoT: Enhancing Granularity and Generalization in Image Editing
Shiyi Zhang, Yiji Cheng, Tiankai Hang +8
Unified multi-modal understanding/generative models have shown improved image editing performance by incorporating fine-grained understanding into their Chain-of-Thought (CoT) proc…
SOAR: Self-Correction for Optimal Alignment and Refinement in Diffusion Models
You Qin, Linqing Wang, Hao Fei +4
The post-training pipeline for diffusion models currently has two stages: supervised fine-tuning (SFT) on curated data and reinforcement learning (RL) with reward models. A fundame…
Hierarchical SVG Tokenization: Learning Compact Visual Programs for Scalable Vector Graphics Modeling
Ximing Xing, Ziteng Xue, Zhenxi Li +8
Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, existing approaches still rely on…
Generative Visual Chain-of-Thought for Image Editing
Zijin Yin, Tiankai Hang, Yiji Cheng +9
Existing image editing methods struggle to perceive where to edit, especially under complex scenes and nuanced spatial instructions. To address this issue, we propose Generative Vi…
PromptEnhancer: A Simple Approach to Enhance Text-to-Image Models via Chain-of-Thought Prompt Rewriting
Linqing Wang, Ximing Xing, Yiji Cheng +13
Recent advancements in text-to-image (T2I) diffusion models have demonstrated remarkable capabilities in generating high-fidelity images. However, these models often struggle to fa…