54 datasets found

Depth completion dataset for industrial objects with RGBD images and ground truth depth.

The KITTI-C dataset is a robustness benchmark for outdoor monocular depth estimation under data corruptions.

A dataset for stereo saliency detection, containing 400 stereo images and estimated depth maps.

A dataset for stereo saliency detection, containing 1985 stereo images and estimated depth maps.

The dataset used for depth estimation and object detection.

Depth estimation in robotic surgery is vital in 3D recon-struction, surgical navigation and augmented reality visualization.

SCARED is one of the MICCAI 2019 challenges, and provided a training set acquired from 7 pigs. Each pig corresponds to 5 videos recorded by a binocular camera from 5 different...

The FlyingThings3D dataset is a benchmark for stereo matching, consisting of a large collection of images and corresponding disparity maps.

The NYUD-v2 dataset is a benchmark for indoor scene segmentation and depth estimation. It contains 1449 images with 4 tasks: semantic segmentation, depth estimation, surface...

Depth-aware Video Panoptic Segmentation (DVPS) is a new challenging vision problem that aims to predict panoptic segmentation and depth in a video simultaneously.

A weakly-supervised depth estimation network using attention mechanism for cases with wrong labels.

The dataset used for training the D2-Net model, consisting of 327,036 image pairs with at least 50% overlap in the sparse SfM point cloud.

The Virtual KITTI dataset is a synthetic dataset, where the virtual scenes are cloned from the real world KITTI video sequences. Besides the 5 virtual image sequences cloned...

The dataset for Symmetry-awareDepthEstimationusingDeepNeuralNetworks, containing product images with reflection symmetry.

Depth from focus (DFF) is a highly ill-posed inverse problem because the optimal focal distance is inferred from sharpness measures which fail in untextured areas. Existing...

The dataset is used for depth estimation from monocular images and sparse radar data.

NYUD2 dataset is a dataset containing RGB-D images for indoor scene understanding. It is used for depth estimation and semantic segmentation tasks.

Relative Depth in Stereo (RDIS) dataset is a dataset containing images labelled with dense relative depths. The ground-truth relative depths are obtained through existing stereo...

The NYUv2 dataset is a large-scale dataset for 3D object recognition and semantic segmentation. It contains 206 test set video sequences with 135 classes.

A medium-scale synthetic 4D LFV dataset that can be used for training deep learning-based methods.