Name: CVPR2022 Pretrained models for ViT
Creator: Hirokatsu Kataoka, Ryo Hayamizu, Ryosuke Yamada, Kodai Nakashima, Sora Takashima, Xinyu Zhang, Edgar Josafat Martinez-Noriega, Nakamasa Inoue, Rio Yokota

Dataset

CVPR2022 Pretrained models for ViT

pre-trained models

vision transformers

NEDO 3.0

This is a set of pre-trained models for Vision Transformers which are trained on ExFractalDB-21k and RCDB-21k.

Detailed Information :https://github.com/masora1030/CVPR2022-Pretrained-ViT-PyTorch

https://drive.google.com/drive/folders/1ikNUxJoMCx3Lx2TMrXfLdIwI6wwK5w_W

Creator :	Hirokatsu Kataoka, Ryo Hayamizu, Ryosuke Yamada, Kodai Nakashima, Sora Takashima, Xinyu Zhang, Edgar Josafat Martinez-Noriega, Nakamasa Inoue, Rio Yokota Contact : rioyokota@gsic.titech.ac.jp
License :	MIT License https://github.com/masora1030/CVPR2022-Pretrained-ViT-PyTorch/blob/main/LICENSE
First Publication Date :	Sun, 12 Jun 2022 JST
Citation :	Hirokatsu Kataoka, Ryo Hayamizu, Ryosuke Yamada, Kodai Nakashima, Sora Takashima, Xinyu Zhang, Edgar Josafat Martinez-Noriega, Nakamasa Inoue, Rio Yokota, Replacing Labeled Real-Image Datasets With Auto-Generated Contours, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern, Recognition (CVPR), pp.21232-21241, 2022.

Updated on Tue, 25 Oct 2022 11:24:40 JST