9 papers
AURORA-LM: Autoencoding Unified Representation for Continuous-Latent Diffusion Language Modeling
Jiajun Liang, Yucheng Liao, Yukang Cao +12
Language remains an outlier in generative modeling: while images, video, and audio are increasingly modeled in continuous latent spaces, text generation still relies predominantly…
Training-free image inversion for one-step diffusion models
Tao Wu, Senmao Li, Yaxing Wang +3
In this work, we introduce a novel training-free inversion (TFinv) framework for one-step diffusion models,addressing key challenges in real image inversion and editing. We first i…
Adversarial Concept Distillation for One-Step Diffusion Personalization
Yixiong Yang, Tao Wu, Senmao Li +4
Recent progress in accelerating text-to-image diffusion models enables high-fidelity synthesis within a single denoising step. However, customizing the fast one-step models remains…
Free-Lunch Color-Texture Disentanglement for Stylized Image Generation
Jiang Qin, Senmao Li, Alexandra Gomez-Villa +4
Recent advances in Text-to-Image (T2I) diffusion models have transformed image generation, enabling significant progress in stylized generation using only a few style reference ima…
From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging
Tao Liu, Dafeng Zhang, Gengchen Li +7
Face aging has become a crucial task in computer vision, with applications ranging from entertainment to healthcare. However, existing methods struggle with achieving a realistic a…
One-Way Ticket:Time-Independent Unified Encoder for Distilling Text-to-Image Diffusion Models
Senmao Li, Lei Wang, Kai Wang +7
Text-to-Image (T2I) diffusion models have made remarkable advancements in generative modeling; however, they face a trade-off between inference speed and image quality, posing chal…