1 citations · 1 across the 10 of their papers we have counts for
10 papers
ExoActor: Exocentric Video Generation as Generalizable Interactive Humanoid Control
Yanghao Zhou, Jingyu Ma, Yibo Peng +3
Humanoid control systems have made significant progress in recent years, yet modeling fluent interaction-rich behavior between a robot, its surrounding environment, and task-releva…
DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning
Yang Zhou, Xiaofeng Wang, Hao Shao +8
Recently, world-action models (WAM) have emerged to bridge vision-language-action (VLA) models and world models, unifying their reasoning and instruction-following capabilities and…
Expert-Choice Routing Enables Adaptive Computation in Diffusion Language Models
Shuibai Zhang, Caspian Zhuang, Chihan Cui +8
Diffusion language models (DLMs) enable parallel, non-autoregressive text generation, yet existing DLM mixture-of-experts (MoE) models inherit token-choice (TC) routing from autore…
UniSync: Towards Generalizable and High-Fidelity Lip Synchronization for Challenging Scenarios
Ruidi Fan, Yang Zhou, Siyuan Wang +3
Lip synchronization aims to generate realistic talking videos that match given audio, which is essential for high-quality video dubbing. However, current methods have fundamental d…
InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions
Mohamed Elmoghany, Liangbing Zhao, Xiaoqian Shen +27
Generating long-form storytelling videos with consistent visual narratives remains a significant challenge in video synthesis. We present a novel framework, dataset, and a model th…
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…
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…
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)…
ActAnywhere: Subject-Aware Video Background Generation
Boxiao Pan, Zhan Xu, Chun-Hao Paul Huang +4
Generating video background that tailors to foreground subject motion is an important problem for the movie industry and visual effects community. This task involves synthesizing b…