collaborators

9 papers

cs.CV2026

Training-Free Image Editing with Visual Context Integration and Concept Alignment

Rui Song, Guo-Hua Wang, Qing-Guo Chen +6

In image editing, it is essential to incorporate a context image to convey the user's precise requirements, such as subject appearance or image style. Existing training-based visua…

cs.CV2026

Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities

Shanshan Zhao, Xinjie Zhang, Jintao Guo +9

Recent years have seen remarkable progress in both multimodal understanding models and image generation models. Despite their respective successes, these two domains have evolved i…

cs.CV2025

Diffusion-SDPO: Safeguarded Direct Preference Optimization for Diffusion Models

Minghao Fu, Guo-Hua Wang, Tianyu Cui +4

Text-to-image diffusion models deliver high-quality images, yet aligning them with human preferences remains challenging. We revisit diffusion-based Direct Preference Optimization…

cs.CV2025

Ovis-Image Technical Report

Guo-Hua Wang, Liangfu Cao, Tianyu Cui +8

We introduce , a 7B text-to-image model specifically optimized for high-quality text rendering, designed to operate efficiently under stringent computational c…

cs.CV2025

Images Speak Louder Than Scores: Failure Mode Escape for Enhancing Generative Quality

Jie Shao, Ke Zhu, Minghao Fu +2

Diffusion models have achieved remarkable progress in class-to-image generation. However, we observe that despite impressive FID scores, state-of-the-art models often generate dist…

cs.CV2025

TeEFusion: Blending Text Embeddings to Distill Classifier-Free Guidance

Minghao Fu, Guo-Hua Wang, Xiaohao Chen +4

Recent advances in text-to-image synthesis largely benefit from sophisticated sampling strategies and classifier-free guidance (CFG) to ensure high-quality generation. However, CFG…