117 datasets found

The dataset used in this paper is the CIFAR-10, ImageNet and CelebA dataset.

The dataset used in the paper is ImageNet, MS COCO, and Pascal VOC datasets.

The dataset used in the paper is the ImageNet-C dataset, which is a dataset of images corrupted with various types of noise and occlusions.

A 1k classes classification task with 1.2M training examples and 50k validation examples. The examples are colour images of various sizes.

The dataset used in the paper is ImageNet-5, ImageNet-20, and ImageNet-100, which are subsets of the ImageNet dataset.

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

The dataset is a benchmark for self-supervised learning on long-tailed data. It contains 115.8K images with 1000 categories, ranging from 1,280 to 5 in terms of class cardinality.

Object recognition is arguably the most important problem at the heart of computer vision. Recently, Barbu et al. introduced a dataset called ObjectNet which includes objects in...

The dataset used in the paper is not explicitly described, but it is mentioned that it is a large-scale captioned image dataset (LAION) used to train the Stable Diffusion model.

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 in the paper is Tiny ImageNet and ImageNet.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used CIFAR-10, CIFAR-100, and ImageNet datasets.

A benchmark for low-shot recognition was proposed by Hariharan & Girshick (2017) and consists of a representation learning phase without access to the low-shot classes and a...

Network calibration aims to accurately estimate the level of confidences, which is particularly important for employing deep neural networks in real-world systems.

The dataset used in the paper is the ImageNet-21k dataset, which is a large-scale hierarchical image database.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used it for language modeling and image classification tasks.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the CLIP model and the CIFAR-10 and ImageNet datasets.