88 datasets found

A face dataset containing images of 83 individuals.

The FaceScrub dataset contains 100K links for online facial images of 530 celebrities.

The BDD100k dataset is a large-scale driving dataset containing 100,000 images of various weather conditions, including clear, rainy, foggy, and night-time.

The V-COCO dataset contains 2,533 training images, 2,867 validation images, and 4,946 test images, including 24 action classes.

The LSUN Bedroom and LSUN Cat dataset is a large-scale image dataset used for training and testing the proposed approach.

The AFHQv2 64×64 dataset is another commonly used image dataset for generative models.

The FFHQ 64×64 dataset is a commonly used image dataset for generative models.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors tested their model on various signal reconstruction tasks: 1D sinusoidal...

The FFHQ dataset is a large dataset of high-quality face images with 1024 × 1024 resolution with variations in age, gender, and glasses.

The dataset used in this paper for testing the 3D-RecGAN++ model. It contains 1.5k SV and 2.5k CV testing datasets for each of the 6 categories.

The dataset used in the paper is a pre-trained ResNet-50 classifier, which is used for image synthesis, unpaired image-to-image translation, and feature similarity estimation.

The dataset consists of a significant collection of 60,000 facial expression images, categorized into eight different classes, including neutral, happy, angry, sad, fear,...

The Face Research London Lab (FRLL) dataset contains images of faces with varying lighting conditions, expressions, and poses.

The Face Recognition Grand Challenge (FRGCv2) dataset contains images of faces with varying lighting conditions, expressions, and poses.

Feature matters for salient object detection. Existing methods mainly focus on designing a sophisticated structure to incorporate multi-level features and filter out cluttered...

The dataset in this paper comes from the database of the Ultrasound Imaging Department of Peking University Shenzhen Hospital.

KITTI 2012 is a real-world dataset in the outdoor scenario, and contains 194 training and 195 testing stereo image pairs with the size of 376 × 1240.

Stereo image super-resolution aims to improve the quality of high-resolution stereo image pairs by exploiting complementary information across views.

HyperKvasir is a comprehensive multi-class image and video dataset for gastrointestinal endoscopy.

The dataset used in this paper is DreamBench, which contains 30 different subject images including backpacks, sneakers, boots, cats, dogs, and toy, etc.