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Wenxu Wu

3 accepted papers

2026

Scaling Multi-Identity Consistency for Image Customization via Multi-to-Multi Matching Paradigm

CVPR 2026

Recent advancements in image customization exhibit a wide range of application prospects due to stronger customization capabilities. However, since we humans are more sensitive to faces, a significant challenge remains in preserving consistent identity while avoiding identity confusion with multi-re

Cited by 0SourcecodeScholar
2026

Unified Customized Generation by Disentangled Reward Modeling

CVPR 2026

Existing literature typically treats various customized generation tasks (e.g., subject-customized generation, style-customized generation) as distinct and disjoint problems, with each task focusing solely on customizing a specific aspect of the reference image. However, we argue that the objectives

Cited by 0SourcecodeScholar
2025

Less-to-More Generalization: Unlocking More Controllability by In-Context Generation

ICCV 2025poster

Although subject-driven generation has been extensively explored in image generation due to its wide applications, it still has challenges in data scalability and subject expansibility. For the first challenge, moving from curating single-subject datasets to multiple-subject ones and scaling them is…