320 datasets found

The dataset used in this paper is ResNet50, ResNet34, and ResNet18.

The dataset used in this paper is VGG19-BN, CIFAR-10, and CIFAR-100.

Object detection is one of the most foundational computer vision task and is essential for many real-world applications. The object detection pipeline has been developed...

The datasets used in the paper are described as follows: WikiMIA, BookMIA, Temporal Wiki, Temporal arXiv, ArXiv-1 month, Multi-Webdata, LAION-MI, Gutenberg.

Recent studies show that Transformer has strong capability of building long-range dependencies, yet is incompetent in capturing high frequencies that predomi- nantly convey...

Large scale multi-view stereopsis evaluation dataset.

The dataset used in this study is a semantic PCB image dataset, which contains images of PCBs with annotated components.

An N-object dataset for testing the proposed framework

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...

Semantic segmentation is one of the fundamental prob-lems in computer vision, whose task is to assign a seman-tic label to each pixel of an image so that different classes can...

The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.

The SCUT-HEAD dataset is a head detection dataset containing images with varying scales and poses.

The Visual Wake Words dataset is a binary classification dataset for detecting the presence of a person in an image.

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

The WIDER FACE dataset is a face detection dataset containing images with varying scales, poses, and occlusions.

A labeled dataset for Malayalam Sign Language (MSL) letters and signs for the identification of static hand gestures specific to Malayalam Sign Language from real-time videos.

Object scene flow is a dataset for stereo matching and optical flow estimation.

Disparity prediction from stereo images is essential to computer vision applications including autonomous driving, 3D model reconstruction, and object detection.

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...

The dataset used in the paper is the KITTI dataset, which is a benchmark for monocular depth estimation. The dataset consists of a large collection of images and corresponding...