Masked autoencoder (MAE), which is based on Transformer architecture, employs a “mask-reconstruction” strategy for training, allowing the model to be effective for downstream tasks. However, existing ...

Let’s move toward the mask autoencoder which will help us in creating a better understanding of the masking of an autoencoder. Mask Autoencoder (MAE) In the above section, we have seen what ...

Unofficial implementation of Masked AutoEncoder (MAE) using PyTorch without using any prebuilt transformer modules. - Ugenteraan/Masked-AutoEncoder-PyTorch. ... About 5k images (labelled) to be used ...

Current model name list: marlin_vit_small_ytf: ViT-small encoder trained on YTF dataset.Embedding 384 dim. marlin_vit_base_ytf: ViT-base encoder trained on YTF dataset.Embedding 768 dim.

This paper proposes a novel approach using the Noisy-Student technique for anomaly detection. It addresses data contamination by combining a density-estimation teacher model for pseudo-labeling with a ...

Masked Image Modeling typically masks parts of the input image or encoded image tokens and promotes the model to reconstruct the masked regions. Many existing Masked Image Modeling methods employ an ...