11 papers
MemLearner: Learning to Query Context memory for Video World Models
Jiwen Yu, Jianxiong Gao, Jianhong Bai +7
Video World Models are interactive video generation models that predict future world states based on user actions and history video frames. A critical challenge in video world mode…
MultiWorld: Scalable Multi-Agent Multi-View Video World Models
Haoyu Wu, Jiwen Yu, Yingtian Zou +1
Video world models have achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled as action-conditioned video gen…
ComSim: Building Scalable Real-World Robot Data Generation via Compositional Simulation
Yiran Qin, Jiahua Ma, Li Kang +11
Recent advancements in foundational models, such as large language models and world models, have greatly enhanced the capabilities of robotics, enabling robots to autonomously perf…
CineScene: Implicit 3D as Effective Scene Representation for Cinematic Video Generation
Kaiyi Huang, Yukun Huang, Yu Li +8
Cinematic video production requires control over scene-subject composition and camera movement, but live-action shooting remains costly due to the need for constructing physical se…
OmniX: From Unified Panoramic Generation and Perception to Graphics-Ready 3D Scenes
Yukun Huang, Jiwen Yu, Yanning Zhou +4
There are two prevalent ways for automatic 3D scene construction: procedural generation and 2D lifting. Among these, panorama-based 2D lifting has emerged as a promising technique,…
GameFactory: Creating New Games with Generative Interactive Videos
Jiwen Yu, Yiran Qin, Xintao Wang +3
Generative videos have the potential to revolutionize game development by autonomously creating new content. In this paper, we present GameFactory, a framework for action-controlle…