6 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…
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…
Context as Memory: Scene-Consistent Interactive Long Video Generation with Memory Retrieval
Jiwen Yu, Jianhong Bai, Yiran Qin +5
Recent advances in interactive video generation have shown promising results, yet existing approaches struggle with scene-consistent memory capabilities in long video generation du…
T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation
Lijun Li, Zhelun Shi, Xuhao Hu +5
Text-to-image (T2I) models have rapidly advanced, enabling the generation of high-quality images from text prompts across various domains. However, these models present notable saf…
Position: Interactive Generative Video as Next-Generation Game Engine
Jiwen Yu, Yiran Qin, Haoxuan Che +5
Modern game development faces significant challenges in creativity and cost due to predetermined content in traditional game engines. Recent breakthroughs in video generation model…
A Survey of Interactive Generative Video
Jiwen Yu, Yiran Qin, Haoxuan Che +7
Interactive Generative Video (IGV) has emerged as a crucial technology in response to the growing demand for high-quality, interactive video content across various domains. In this…