Visual General Intelligence: A White Paper

2026-08-26

AI Summary

本文探讨了视觉模态在通向通用人工智能(AGI)路径上的潜力，通过分析视觉智能的定义、原则、输入形式、基准及与其他模态如语言的关系。

Abstract

This paper reconsiders intelligence from a vision-centered perspective and examines whether intelligence emerging from visual experience and learning may provide a pathway toward AGI. In the language domain, beginning with the introduction of the Transformer architecture, the GPT series has demonstrated transfer to unseen tasks through autoregressive language modeling on web-scale text combined with aggressive scaling. This raises a natural question, namely, what capabilities and forms of intelligence can emerge from visual modalities such as images, videos, and geometry? In this paper, we discuss whether visual intelligence can serve as a pathway toward AGI, referred to in this paper as visual general intelligence (VGI), by bringing together contributors from diverse standpoints and affiliations. Our aim is not to offer a single definition of visual intelligence, but to clarify the principles that computer vision should pursue in the AGI era, the visual input modalities, the benchmarks, the learning paradigms, and the relationship between vision, when taken as the core, and other modalities such as language.

Problem

• Visual General Intelligence
• AGI
• visual modalities

Innovation

• Visual General Intelligence
• Vision-centered Perspective
• Autoregressive Modeling
• Web-scale Learning
• Intelligence from Visual Experience