ViT
Transformer that treats an image as a sequence of patches.
Aperçu
ViT splits an image into fixed-size patches, embeds each as a token, and processes the sequence with an ordinary transformer. It solves the problem that convolutional architectures bake in assumptions about locality that a large enough model does not need. It exists because it showed that the architecture which won in language transfers to vision once there is enough data, which removed the main reason the two fields had different toolkits.
Graphe des technologies
Comment ViT se rattache au reste de la pile.
Utilise et dépend de
- Transformer architecture Algorithms ViT based on Transformer High ✓ source
Appliqué à
- Multimodal AI application Multimodal ViT used for Multimodal AI High ✓ source
Alternatives
Comparaisons
Comparaisons détaillées avec les alternatives ci-dessus.