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20232026
most citedAttnDreamBooth: Towards Text-Aligned Personalized Text-to-Image Generation

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cs.CV2026

MaskAlign: Token-Subset Representation Alignment for Efficient Diffusion Training

Lianyu Pang, Tianlin Pan, Cheng Da +5

Representation alignment with pretrained vision models has recently shown strong potential for accelerating diffusion transformer training. By aligning intermediate diffusion featu…

cs.CV2025

Training for Identity, Inference for Controllability: A Unified Approach to Tuning-Free Face Personalization

Lianyu Pang, Ji Zhou, Qiping Wang +4

Tuning-free face personalization methods have developed along two distinct paradigms: text embedding approaches that map facial features into the text embedding space, and adapter-…

cs.CV2024

CoRe: Context-Regularized Text Embedding Learning for Text-to-Image Personalization

Feize Wu, Yun Pang, Junyi Zhang +5

Recent advances in text-to-image personalization have enabled high-quality and controllable image synthesis for user-provided concepts. However, existing methods still struggle to…

cs.CV20241 cited

AttnDreamBooth: Towards Text-Aligned Personalized Text-to-Image Generation

Lianyu Pang, Jian Yin, Baoquan Zhao +4

Recent advances in text-to-image models have enabled high-quality personalized image synthesis of user-provided concepts with flexible textual control. In this work, we analyze the…

cs.CV2023

Cross Initialization for Personalized Text-to-Image Generation

Lianyu Pang, Jian Yin, Haoran Xie +3

Recently, there has been a surge in face personalization techniques, benefiting from the advanced capabilities of pretrained text-to-image diffusion models. Among these, a notable…