9 citations · 11 across the 6 of their papers we have counts for
6 papers
HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers
Guozhen Zhang, Xuerui Qiu, Yutao Cui +11
Holistic visual tokenizers are fundamental to unified multimodal models (UMMs) as they map diverse visual inputs into a unified representation space. In this paper, we present HYDR…
DisCa: Accelerating Video Diffusion Transformers with Distillation-Compatible Learnable Feature Caching
Chang Zou, Changlin Li, Yang Li +7
While diffusion models have achieved great success in the field of video generation, this progress is accompanied by a rapidly escalating computational burden. Among the existing a…
Prompt-aware classifier free guidance for diffusion models
Xuanhao Zhang, Chang Li
Diffusion models have achieved remarkable progress in image and audio generation, largely due to Classifier-Free Guidance. However, the choice of guidance scale remains underexplor…
HunyuanVideo: A Systematic Framework For Large Video Generative Models
Weijie Kong, Qi Tian, Zijian Zhang +49
Recent advancements in video generation have significantly impacted daily life for both individuals and industries. However, the leading video generation models remain closed-sourc…
Ada-adapter:Fast Few-shot Style Personlization of Diffusion Model with Pre-trained Image Encoder
Jia Liu, Changlin Li, Qirui Sun +5
Fine-tuning advanced diffusion models for high-quality image stylization usually requires large training datasets and substantial computational resources, hindering their practical…
Perception-Oriented Video Frame Interpolation via Asymmetric Blending
Guangyang Wu, Xin Tao, Changlin Li +3
Previous methods for Video Frame Interpolation (VFI) have encountered challenges, notably the manifestation of blur and ghosting effects. These issues can be traced back to two piv…