DETR
DETR (DEtection TRansformer) is an end-to-end object detection model that reframes detection as a direct set prediction problem solved with a transformer encoder-decoder and bipartite matching, removing the…
Transformer Models
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DeiT
DeiT (Data-efficient Image Transformers) is a family of vision transformer models that proved Vision Transformers can be trained to state-of-the-art image classification accuracy on ImageNet alone
Hiera
Hiera is a hierarchical vision transformer from Meta AI (FAIR), introduced in the paper "Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles" presented as an oral at the International…
Masked autoencoder (MAE)
Masked autoencoder (MAE) is a self-supervised learning method for vision transformers that masks roughly 75% of an input image's patches and trains a network to reconstruct the missing pixels from the small…
Swin Transformer
The Swin Transformer (Shifted Window Transformer) is a hierarchical vision transformer architecture that computes self-attention within local, non-overlapping windows and introduces a shifted window…