Foundation Models

Vision Encoder

A vision encoder is the neural network component that maps raw images into compact feature embeddings consumed by downstream policy, planning, or reasoning modules. Common choices in robot learning include convolutional backbones such as ResNet and transformer backbones such as ViT, often pretrained with objectives like CLIP, SigLIP, or DINOv2; vision-language-action models typically fuse one or more vision encoders with a language-model backbone.

Why it matters for physical AI

Encoder choice and pretraining largely determine what a robot policy can perceive, and reusing frozen web-pretrained encoders is one of the main mechanisms by which internet-scale visual knowledge transfers into physical skills.