Interactive panoramic video generation aims to synthesize immersive 360\textdegree{} videos that remain visually coherent while following user-specified camera trajectories during exploration. However, progress is limited by a coupled data-and-model gap: existing panoramic video datasets are often short, weakly annotat...
Jia-Ming Tan, Zhen Li, Shu-Wei Shi et al.· 0 citations
Building interactive worlds that respond coherently to player actions has long been a shared goal of computer graphics, games, and artificial intelligence. Recent video generative models provide a data-driven route toward this goal by predicting future observations conditioned on user actions, and are increasingly rega...
Zhen Li, Zian Meng, Shuwei Shi et al.· arXiv.org· 2 citations
This work introduces Surprise Forcing, a training-free framework that treats both limitations as online resource-allocation problems and improves long-horizon consistency and visual quality while retaining real-time streaming throughput.