5 papers
Beyond Text Prompts: Visual-to-Visual Generation as A Unified Paradigm
Yaofang Liu, Kangning Cui, Meng Chu +7
Humans often specify and create through visual artifacts: typography sheets, sketches, reference images, and annotated scenes. Yet modern visual generators still ask users to seria…
Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation
Yaofang Liu, Yumeng Ren, Aitor Artola +9
The rapid advancement of video diffusion models has been hindered by fundamental limitations in temporal modeling, particularly the rigid synchronization of frame evolution imposed…
Improving Diffusion Generative Models via Truncated Karhunen--Loève Expansion
Yumeng Ren, Yaofang Liu, Aitor Artola +3
Pretrained diffusion models exhibit a well-known training-sampling mismatch, often attributed to exposure bias and related distribution-shift effects. We provide a quantitative int…
Super-resolving Real-world Image Illumination Enhancement: A New Dataset and A Conditional Diffusion Model
Yang Liu, Yaofang Liu, Jinshan Pan +4
Most existing super-resolution methods and datasets have been developed to improve the image quality in well-lighted conditions. However, these methods do not work well in real-wor…
Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approach
Yaofang Liu, Yumeng Ren, Xiaodong Cun +5
Diffusion models have revolutionized image generation, and their extension to video generation has shown promise. However, current video diffusion models~(VDMs) rely on a scalar ti…