992 datasets found

FFHQ-UV: a large-scale 3D Morphable Models (3DMMs)-based facial UV-texture dataset derived from a natural image dataset FFHQ.

Zero-shot learning (ZSL) aims to classify objects that are not observed or seen during training. It relies on class semantic description to transfer knowledge from the seen...

Synthetic rainy images dataset for training and testing the proposed LPNet for single image deraining.

The dataset for single image deraining, containing images with rain and their corresponding ground truth images.

Dense pixel matching is required for many computer vision algorithms such as disparity, optical flow or scene flow estimation. Feature Pyramid Networks (FPN) have proven to be a...

SemanticKitti is a large-scale street view point cloud dataset for 3D semantic segmentation.

PointConvFormer is a novel point cloud layer that combines ideas from point convolution and transformers.

The CIFAR-10 and CIFAR-100 datasets are used to evaluate the performance of the commentaries curriculum.

Oxford 102 Flowers is a dataset of images of different flower species.

ConvNet-AIG is a convolutional network that adaptsively defines its network topology conditioned on the input image.

The Market-1501 dataset is a large-scale benchmark for person re-identification.

The EyePACS dataset consists of 35,126 training images and 53,576 testing images only containing grading labels.

Tursun et al.'s dataset is used for testing the proposed HDR-Transformer.

Sen et al.'s dataset is used for testing the proposed HDR-Transformer.

Kalantari et al.'s dataset consists of 74 samples for training and 15 samples for testing.

A deep learning model that learns subject-level representation from a set of local features. The model represents the image volume as a bag (or set) of local features and can...

The dataset used in the paper is a Sintel dataset, which consists of low-resolution optical flow maps and their corresponding high-resolution RGB images.

Structural Vision Transformer (StructViT) is a vision transformer network that leverages structural self-attention (StructSA) to capture correlation structures in images and...

Dataset for waste classification using computer vision and deep learning

The Pix3D dataset is a collection of 3D models with RGB images, used for training and testing 3D object recognition and generation tasks.