1,082 datasets found

The dataset is used for automatic method for detecting Age-related Macular Degeneration (AMD) lesions in RGB eye fundus images.

MaX-DeepLab: End-to-end panoptic segmentation with mask transformers

Convolutional network are the de-facto standard for analysing spatio-temporal data such as images, videos, 3D shapes, etc. Whilst some of this data is naturally dense (for...

Breast cancer histology images classification using transfer learning

The MS COCO dataset is a large benchmark for image captioning, containing 328K images with 5 caption descriptions each.

The dataset used in the paper for layout sequence prediction from noisy mobile modality.

The ImageNet dataset is a large-scale image database that contains over 14 million images, each labeled with one of 21,841 categories.

A benchmark for stereo matching and depth estimation.

Mobile Video Networks (MoViNets) is a family of computation and memory efficient video networks that can operate on streaming video for online inference.

Hyperhuman dataset for 3D face rendering

The COD10K dataset is currently the largest challenging dataset for COD, containing 10K images with dense annotations.

MonoDiffusion: A novel self-supervised monocular depth estimation framework by reformulating it as an iterative denoising process.

NeRF LLFF dataset is a benchmark dataset for learning implicit 3D representations and addressing different tasks such as novel-view synthesis or depth-map estimation.

Power line maintenance and inspection are essential to avoid power supply interrup- tions, reducing its high social and financial impacts yearly. Automating power line visual...

Monocular depth estimation is a fundamental knowledge for autonomous systems that need to assess their own state and perceive the surrounding environment.

The Omniglot dataset consists of 100 classes, each containing 20 images. Ten images were taken from each class for augmentation, and the rest were used as the test set. Each...

A dataset of ImageNet images with subtle 3D perspective changes that can break ImageNet-trained classification networks.

A dataset of complex image data with a fixed, known distribution, generated using a computer graphics pipeline.

The dataset used for the experiments of the paper "CORE-PERIPHERY PRINCIPLE GUIDED REDISIGN OF SELF-ATTENTION IN TRANSFORMERS"

The Blender dataset consists of 8 synthetic 3D scenes, each with a hundred posed images of resolution 800 × 800.