AnimeGamer: Infinite Anime Life Simulation with Next Game State
  Prediction
Authors: name: Junhao Cheng; name: Yuying Ge; name: Yixiao Ge; name: Jing Liao; name: Ying Shan
Published: 2025-04-01 17:57:18

Abstract: Recent advancements in image and video synthesis have opened up new promise
in generative games. One particularly intriguing application is transforming
characters from anime films into interactive, playable entities. This allows
players to immerse themselves in the dynamic anime world as their favorite
characters for life simulation through language instructions. Such games are
defined as infinite game since they eliminate predetermined boundaries and
fixed gameplay rules, where players can interact with the game world through
open-ended language and experience ever-evolving storylines and environments.
Recently, a pioneering approach for infinite anime life simulation employs
large language models (LLMs) to translate multi-turn text dialogues into
language instructions for image generation. However, it neglects historical
visual context, leading to inconsistent gameplay. Furthermore, it only
generates static images, failing to incorporate the dynamics necessary for an
engaging gaming experience. In this work, we propose AnimeGamer, which is built
upon Multimodal Large Language Models (MLLMs) to generate each game state,
including dynamic animation shots that depict character movements and updates
to character states, as illustrated in Figure 1. We introduce novel
action-aware multimodal representations to represent animation shots, which can
be decoded into high-quality video clips using a video diffusion model. By
taking historical animation shot representations as context and predicting
subsequent representations, AnimeGamer can generate games with contextual
consistency and satisfactory dynamics. Extensive evaluations using both
automated metrics and human evaluations demonstrate that AnimeGamer outperforms
existing methods in various aspects of the gaming experience. Codes and
checkpoints are available at https://github.com/TencentARC/AnimeGamer.