What is Patch Embedding?

Why does Patch Embedding matter?

It creates the interface between a spatial image grid and a sequence model, with patch size controlling token count and retained local detail.

Patch Embedding in practice

Record patch and image dimensions, handle padding or resizing explicitly, add position information, and measure how resolution changes affect both accuracy and token cost.

What is the common confusion about Patch Embedding?

A patch embedding is the vector representation of a patch, not a semantic object detector or a guarantee that patch boundaries match visual entities.

Learn Patch Embedding in the course

Start with

• Vision Transformers and the Patch-Token Primitive

  Before anything multimodal, an image has to become a sequence of tokens a transformer can eat. The 2020 ViT paper answered this with 16x16 pixel patches, a linear projection, and a position embedding.

  Phase 12: Multimodal AI

Lessons that name Patch Embedding in a title or section

• Vision Transformers (ViT)

  Cut the image into patches, treat each patch as a word, run a standard transformer. Don't look back. Implement patch embedding, learned positional embedding, class token, and transformer encoder…

  Phase 04: Computer Vision

Taught in Phase 12: Multimodal AI.

Also covered in Phase 04: Computer Vision.

Related terms

• Vision Transformer (ViT)A vision architecture that represents an image as a sequence of patch embeddings with position information and processes that sequence…
• Image TokenA model-specific visual unit represented as a vector or discrete code, commonly derived from an image patch, region, or learned…
• EmbeddingA learned mapping from discrete items (words, images, users) to dense vectors in continuous space, where similar items end up close together
• TokenAn integer identifier produced by a model-specific tokenizer from text, bytes, images, audio, or another input representation.

Sources

• An Image is Worth 16x16 Words

More terms in Multimodal systems

• Audio Token
• Automatic Speech Recognition (ASR)
• Cross-Attention
• Early Fusion
• Image Token
• Late Fusion
• Modality
• Modality Alignment
• Multimodal Fusion
• Multimodal Model
• Shared Embedding Space
• Vision-Language Model (VLM)
• Vision Transformer (ViT)
• Visual Grounding

Open the Multimodal systems list in the glossary