Official DeiT repository. Contribute to facebookresearch/deit development by creating an account on GitHub.

Aimv2 BEiT BiT Conditional DETR ConvNeXT ConvNeXTV2 CvT D-FINE DAB-DETR Deformable DETR DeiT Depth Anything Depth Anything V2 DepthPro DETA DETR DiNAT DINOV2 …

Dec 23, 2020 · Our new technique — Data-efficient image Transformers (DeiT) — requires far less data and far less computing resources to produce a high-performance image …

Feb 9, 2025 · Data-Efficient Image Transformer (DeiT) [1] is a significant step forward from the original Vision Transformer (ViT) [2] by addressing its major shortcoming: the reliance on …

Dec 23, 2020 · Recently, neural networks purely based on attention were shown to address image understanding tasks such as image classification. However, these visual transformers …

Introduced to address the challenge of achieving strong performance with limited labeled data, DeiT leverages distillation techniques and large-scale unlabeled datasets during training.

DeiT is among the first works to show that it's possible to train ViTs well without using larger datasets. In this example, we implement the distillation recipe proposed in DeiT.

Oct 17, 2024 · DeiT is a new VIT method to handle the problem of VIT requiring a large amount of data. It incorporates a distillation token and learns from the teacher model's prediction to …

Mar 2, 2022 · The innovation of DeiT is proposes a new distillation process based on a distillation token, which has the same function as a class token. It is a token added after the image block …

Data-efficient Image Transformer (DeiT) model pre-trained and fine-tuned on ImageNet-1k (1 million images, 1,000 classes) at resolution 224x224. It was first introduced in the paper …