5 papers
Fast Image Super-Resolution via Consistency Rectified Flow
Jiaqi Xu, Wenbo Li, Haoze Sun +8
Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step sampling largely hinders thei…
Veda: Scalable Video Diffusion via Distilled Sparse Attention
Shihao Han, Hao Yang, Xinting Hu +3
Scaling Diffusion Transformers to generate high-resolution, long videos is constrained by the quadratic cost of self-attention, and existing sparse attention methods degrade under…
Waver: Wave Your Way to Lifelike Video Generation
Yifu Zhang, Hao Yang, Yuqi Zhang +7
We present Waver, a high-performance foundation model for unified image and video generation. Waver can directly generate videos with durations ranging from 5 to 10 seconds at a na…
LLIA -- Enabling Low-Latency Interactive Avatars: Real-Time Audio-Driven Portrait Video Generation with Diffusion Models
Haojie Yu, Zhaonian Wang, Yihan Pan +7
Diffusion-based models have gained wide adoption in the virtual human generation due to their outstanding expressiveness. However, their substantial computational requirements have…
Goku: Flow Based Video Generative Foundation Models
Shoufa Chen, Chongjian Ge, Yuqi Zhang +19
This paper introduces Goku, a state-of-the-art family of joint image-and-video generation models leveraging rectified flow Transformers to achieve industry-leading performance. We…