With the recent advancement in large language models (LLMs), there is a
growing interest in combining LLMs with multimodal learning. Previous surveys
of multimodal large language models (MLLMs) mainly focus on understanding. This
survey elaborates on multimodal generation across different domains, including
image, video, 3D, and audio, where we highlight the notable advancements with
milestone works in these fields. Specifically, we exhaustively investigate the
key technical components behind methods and multimodal datasets utilized in
these studies. Moreover, we dig into tool-augmented multimodal agents that can
use existing generative models for human-computer interaction. Lastly, we also
comprehensively discuss the advancement in AI safety and investigate emerging
applications as well as future prospects. Our work provides a systematic and
insightful overview of multimodal generation, which is expected to advance the
development of Artificial Intelligence for Generative Content (AIGC) and world
models. A curated list of all related papers can be found at
this https URL

多模态生成技术的调查，介绍了不同领域中的重要进展，包括图像、视频、3D 和音频，研究了方法和数据集，还提出了使用现有生成模型进行人机交互的工具增强型多模态代理，同时探讨了人工智能安全问题和新兴应用及未来前景。