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20242026
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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…