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CAE v2: Context Autoencoder with CLIP Target
Masked image modeling (MIM) learns visual representation by masking and reconstructing image patches. Applying the reconstruction supervision on the CLIP representation has been... -
Microsoft COCO Dataset
The MS COCO 2014 Dataset contains images of 91 object categories, which contains 82783 training images, 40504 validation images and 40775 testing images. -
No Token Left Behind: Explainability-Aided Image Classification and Generation
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the ImageNet, ImageNetV2, ImageNet-Sketch, ImageNet-A, and Imagenet-R datasets. -
Oxford Flower
The Oxford Flower dataset is a collection of 2,000 images of flowers in 80 classes. -
ImageNet Validation Set
The dataset used in the paper is the ImageNet validation set, a subset of the ImageNet dataset. -
ImageNet-1K, Food-101, Birds, and Dogs datasets
The dataset used for image classification tasks, including ImageNet-1K, Food-101, Birds, and Dogs. -
Places dataset
The Places dataset is a large-scale dataset for scene recognition, containing 1 million images from 365 categories. -
CIFAR-10 and Fashion-MNIST
The dataset used in the paper is CIFAR-10 and Fashion-MNIST. -
Stanford Cars dataset
The Stanford Cars dataset is a dataset of images of cars, with 196 categories and approximately 16,000 images. The authors created a synthetic dataset by adding occlusions of... -
FashionMNIST dataset
The dataset used in this paper is the FashionMNIST dataset, which consists of 60,000 images of clothing items from 10 different classes. -
Sub-ImageNet dataset
Sub-ImageNet dataset consists of 60,000 training and 10,000 testing samples. -
CIFAR10 dataset
The dataset used in this paper is the CIFAR10 dataset, which contains 60,000 32x32 color images in 10 classes, with 6,000 images per class. -
MNIST and SVHN datasets
MNIST dataset consists of 60,000 training and 10,000 testing samples, while SVHN consists of 73,257 training and 26,032 testing digital images. -
ResMLP-S12
The ResMLP-S12 dataset is used for image classification tasks. -
Contrast Enhanced CT Phase Classification
Computed Tomography (CT) dataset for contrast phase classification -
Diffusion Denoised Smoothing
Diffusion Denoised Smoothing (DDS) requires no new technical ideas on top of what was introduced in the section above. -
Tiny-Imagenet
Tiny-Imagenet is a dataset of 100,000 224x224 color images, each belonging to one of 200 classes.
