7 papers
Progressive Autoregressive Video Diffusion Models
Desai Xie, Zhan Xu, Yicong Hong +5
Current frontier video diffusion models have demonstrated remarkable results at generating high-quality videos. However, they can only generate short video clips, normally around 1…
Visual Persona: Foundation Model for Full-Body Human Customization
Jisu Nam, Soowon Son, Zhan Xu +6
We introduce Visual Persona, a foundation model for text-to-image full-body human customization that, given a single in-the-wild human image, generates diverse images of the indivi…
Move-in-2D: 2D-Conditioned Human Motion Generation
Hsin-Ping Huang, Yang Zhou, Jui-Hsien Wang +4
Generating realistic human videos remains a challenging task, with the most effective methods currently relying on a human motion sequence as a control signal. Existing approaches…
HARIVO: Harnessing Text-to-Image Models for Video Generation
Mingi Kwon, Seoung Wug Oh, Yang Zhou +6
We present a method to create diffusion-based video models from pretrained Text-to-Image (T2I) models. Recently, AnimateDiff proposed freezing the T2I model while only training tem…
Customize-A-Video: One-Shot Motion Customization of Text-to-Video Diffusion Models
Yixuan Ren, Yang Zhou, Jimei Yang +5
Image customization has been extensively studied in text-to-image (T2I) diffusion models, leading to impressive outcomes and applications. With the emergence of text-to-video (T2V)…
SNED: Superposition Network Architecture Search for Efficient Video Diffusion Model
Zhengang Li, Yan Kang, Yuchen Liu +4
While AI-generated content has garnered significant attention, achieving photo-realistic video synthesis remains a formidable challenge. Despite the promising advances in diffusion…