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20232026
most citedFreeTuner: Any Subject in Any Style with Training-free Diffusion

1 citations · 1 across the 24 of their papers we have counts for

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cs.CV2025

FlowDC: Flow-Based Decoupling-Decay for Complex Image Editing

Yilei Jiang, Zhen Wang, Yanghao Wang +4

With the surge of pre-trained text-to-image flow matching models, text-based image editing performance has gained remarkable improvement, especially for \underline{simple editing}…

cs.CV2025

CoMo: Compositional Motion Customization for Text-to-Video Generation

Youcan Xu, Zhen Wang, Jiaxin Shi +6

While recent text-to-video models excel at generating diverse scenes, they struggle with precise motion control, particularly for complex, multi-subject motions. Although methods f…

cs.CV2025

Target-aware Image Editing via Cycle-consistent Constraints

Yanghao Wang, Zhen Wang, Long Chen

Recent pre-trained text-to-image flow models have enabled remarkable progress in text-based image editing. Mainstream approaches adopt a corruption-then-restoration paradigm, where…

cs.CV2025

FastFit: Accelerating Multi-Reference Virtual Try-On via Cacheable Diffusion Models

Zheng Chong, Yanwei Lei, Shiyue Zhang +7

Despite its great potential, virtual try-on technology is hindered from real-world application by two major challenges: the inability of current methods to support multi-reference…

cs.CV2025

Zero-Residual Concept Erasure via Progressive Alignment in Text-to-Image Model

Hongxu Chen, Zhen Wang, Taoran Mei +4

Concept Erasure, which aims to prevent pretrained text-to-image models from generating content associated with semantic-harmful concepts (i.e., target concepts), is getting increas…

cs.CV2025

Diffusion Restoration Adapter for Real-World Image Restoration

Hanbang Liang, Zhen Wang, Weihui Deng

Diffusion models have demonstrated their powerful image generation capabilities, effectively fitting highly complex image distributions. These models can serve as strong priors for…