9 papers
RefAlign: Representation Alignment for Reference-to-Video Generation
Lei Wang, YuXin Song, Ge Wu +5
Reference-to-video (R2V) generation is a controllable video synthesis paradigm that constrains the generation process using both text prompts and reference images, enabling applica…
FasterVAR: Plug-and-Play Acceleration for Visual Autoregressive Models
Senmao Li, Kai Wang, Salman Khan +3
Visual Autoregressive (VAR) modeling departs from the next-token prediction paradigm of traditional Autoregressive (AR) models through next-scale prediction, enabling high-quality…
Anchor Token Matching: Implicit Structure Locking for Training-free AR Image Editing
Taihang Hu, Linxuan Li, Kai Wang +3
Text-to-image generation has seen groundbreaking advancements with diffusion models, enabling high-fidelity synthesis and precise image editing through cross-attention manipulation…
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…
Not All Parameters Matter: Masking Diffusion Models for Enhancing Generation Ability
Lei Wang, Senmao Li, Fei Yang +5
The diffusion models, in early stages focus on constructing basic image structures, while the refined details, including local features and textures, are generated in later stages.…
InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration
Senmao Li, Kai Wang, Joost van de Weijer +6
Diffusion priors have been used for blind face restoration (BFR) by fine-tuning diffusion models (DMs) on restoration datasets to recover low-quality images. However, the naive app…