992 datasets found

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the ImageNet, Places205, and VOC07 datasets for evaluation.

Dataset used for training and testing Convolutional Neural Networks for detecting trypophobia triggers.

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

The COCO keypoint benchmark is a widely used dataset for human pose estimation.

Multi-person pose estimation is a fundamental yet challenging task in computer vision. Both rich context information and spatial information are required to precisely locate the...

The dataset used in the paper for testing the GaMeS model, containing images of six people, generated using Blender software from various perspectives, excluding the backs of...

The dataset used in the paper for testing the GaMeS model, containing 5 outdoor and 4 indoor scenes, each featuring intricate central objects or areas against detailed backgrounds.

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

Skin cancer is one of the most common types of cancer in the world. Different computer-aided diagnosis systems have been proposed to tackle skin lesion diagnosis, most of them...

Vision Big Bird: Random Sparsification for Full Attention

Learning from bounding-boxes annotations has shown great potential in weakly-supervised 3D point cloud instance segmentation. However, we observed that existing methods would...

The Youtube Faces (YTF) dataset contains 3,424 videos belonging to 1,595 different identities.

The Labeled Face in the Wild (LFW) dataset contains 13,233 facial images belonging to 5,749 different individuals.

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

The RESIDE dataset is a large-scale dataset for benchmarking single image dehazing algorithms, and it includes both indoor and outdoor hazy images.

Pyramid VisionLLaMA: A versatile backbone for dense prediction without convolutions.

Conditional positional encodings for vision transformers.

Twins: Revisiting the design of spatial attention in vision transformers.

Mobilevlm: A fast, reproducible and strong vision language assistant for mobile devices.

VisionLLaMA is a unified and generic modeling framework for solving most vision tasks.