From the 1 of 6 linked papers with an AI index.
6 papers
Surprise Forcing: What to Remember, When to Skip in Long Video Generation
Shuwei Shi, Zhen Li, Muyao Niu +4
Streaming autoregressive diffusion makes minute-scale video synthesis practical, but its bounded context and fixed denoising schedule allocate resources uniformly across a highly n…
From Pixels to States: Rethinking Interactive World Models as Game Engines
Zhen Li, Zian Meng, Shuwei Shi +4
The paper surveys how recent video generative models can be used to build interactive game worlds, analyzing four key dimensions of game engine design and introducing a large datas…
WildWorld: A Large-Scale Dataset for Dynamic World Modeling with Actions and Explicit State toward Generative ARPG
Zhen Li, Zian Meng, Shuwei Shi +5
Dynamical systems theory and reinforcement learning view world evolution as latent-state dynamics driven by actions, with visual observations providing partial information about th…
MotionStone: Decoupled Motion Intensity Modulation with Diffusion Transformer for Image-to-Video Generation
Shuwei Shi, Biao Gong, Xi Chen +9
The image-to-video (I2V) generation is conditioned on the static image, which has been enhanced recently by the motion intensity as an additional control signal. These motion-aware…
Mimir: Improving Video Diffusion Models for Precise Text Understanding
Shuai Tan, Biao Gong, Yutong Feng +6
Text serves as the key control signal in video generation due to its narrative nature. To render text descriptions into video clips, current video diffusion models borrow features…
ResMaster: Mastering High-Resolution Image Generation via Structural and Fine-Grained Guidance
Shuwei Shi, Wenbo Li, Yuechen Zhang +3
Diffusion models excel at producing high-quality images; however, scaling to higher resolutions, such as 4K, often results in over-smoothed content, structural distortions, and rep…