We propose MM-REACT, a system paradigm that integrates ChatGPT with a pool of
vision experts to achieve multimodal reasoning and action. In this paper, we
define and explore a comprehensive list of advanced vision tasks that are
intriguing to solve, but may exceed the capabilities of existing vision and
vision-language models. To achieve such advanced visual intelligence, MM-REACT
introduces a textual prompt design that can represent text descriptions,
textualized spatial coordinates, and aligned file names for dense visual
signals such as images and videos. MM-REACT's prompt design allows language
models to accept, associate, and process multimodal information, thereby
facilitating the synergetic combination of ChatGPT and various vision experts.
Zero-shot experiments demonstrate MM-REACT's effectiveness in addressing the
specified capabilities of interests and its wide application in different
scenarios that require advanced visual understanding. Furthermore, we discuss
and compare MM-REACT's system paradigm with an alternative approach that
extends language models for multimodal scenarios through joint finetuning.
Code, demo, video, and visualization are available at
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MM-REACT 是一种系统范例，将 ChatGPT 与一组视觉专家集成在一起，以实现多模态推理和动作，并引入了文本提示设计，以表示文本描述、已文本化的空间坐标和对齐的文件名来处理多模态信息。