492 datasets found

The dataset used in this paper is the VGG16 dataset, a deep neural network trained on the CIFAR-10 and CIFAR-100 datasets.

The dataset used in this paper is the ResNet50 dataset, a deep neural network trained on the ImageNet dataset.

The dataset used in the paper is PASCAL VOC2007 test dataset and VOC2012 trainval datasets.

The dataset used in the paper is ImageNet-Dogs15, a subset of ImageNet containing 15 dog breeds.

The dataset used in this paper is a neural network, and the authors used it to test the performance of their lookahead pruning method.

CUB-200 is a fine-grained image classification dataset containing high resolution images of 200 different bird species.

A synthetic image dataset generated with Stable Diffusion using the Wordnet taxonomy and the definitions of concepts it contains.

Tiny Images dataset is a large dataset of images, each with a small size.

Privacy-preserving image classification method that uses ViT and a block-wise encryption method

FER2013 is a crowdsourced dataset. Each image was individually labeled by 40 taggers for the sake of rigor.

Large-scale vision-and-language models trained on curated and web-scrapped data have led to significant improvements over task-specific models when transferred to downstream...

The dataset used in the paper is the ILSVRC2012 dataset, which contains images of size 224x224.

The dataset used in the paper is a cross-domain dataset, consisting of six domains: Real, Painting, Sketch, Clipart, Infograph, and Quickdraw. Each domain contains 345 object...

The ImageNet-10 dataset is a subset of the ImageNet-1K dataset, containing images from 10 classes.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.

The dataset used in the paper is Tiny ImageNet and ImageNet.

The dataset used in the paper is CIFAR-10 and ImageNet-100.

Instance segmentation (IS) is an important computer vision task, aiming at simultaneously predicting the class label and the binary mask for each instance of interest in an image.

The Cityscapes dataset is a large and famous city street scene semantic segmentation dataset. 19 classes of which 30 classes of this dataset are considered for training and...