15 datasets found

The dataset used in the paper is not explicitly described, but it is mentioned that it is a visual recognition task.

Contextual convolution (CoConv) for visual recognition. CoConv is a direct replacement of the standard convolution that can be used at any stage in CNN architectures.

The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset is a large-scale image classification dataset containing over 14 million images from 21,841 categories.

The dataset used in the paper is a set of visual recognition tasks, spanning both the data-abundant and data-limited regimes.

This dataset is used to evaluate the performance of a Convolutional Neural Network (CNN) on the ImageNet Large Scale Visual Recognition Challenge (ILSVRC2012).

This dataset is used to evaluate the performance of a Convolutional Neural Network (CNN) on the ImageNet Large Scale Visual Recognition Challenge (ILSVRC2012).

MiniImageNet, Caltech-UCSD Birds 200-2011, TieredImageNet, OfficeHome

Visual recognition in a low-data regime is challenging and often prone to overfitting. To mitigate this issue, several data augmentation strategies have been proposed. However,...

The Deep High-Resolution Representation Learning for Visual Recognition dataset.

The dataset used in the paper is the Imagenet dataset, which is a large annotated dataset of images used for image classification tasks.

The dataset used in the paper is the ImageNet 2012 Large-Scale Visual Recognition Challenge dataset.

The OfficeHome dataset is a benchmark for domain generalization, containing 13,000 images from 6 domains: Clipart, Product, Real World, Art, Product, and Real World.

The iNaturalist2018 dataset is the largest dataset for long-tailed visual recognition.

The Microsoft COCO dataset was used for training and evaluating the CNNs because it has become a standard benchmark for testing algorithms aimed at scene understanding and...

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...