Depth in the Wild is a dataset for single-image depth perception in the wild, i.e., recovering depth from a single image taken in unconstrained settings. It ...
Depth estimation datasets are used to train a model to approximate the relative distance of every pixel in an image from the camera, also known as depth. The ...
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The KITTI-Depth dataset includes depth maps from projected LiDAR point clouds that were matched against the depth estimation from the stereo cameras.
The most diverse dataset for depth estimation with metric depth information with 750,000 images. 50,000 image clusters cover varying geographical areas globally.
Estimate Depth of the Image Using Deep learning.
It is comprised of pairs of RGB and Depth frames that have been synchronized and annotated with dense labels for every image. In addition to the projected depth ...
We introduce an RGB-D scene dataset consisting of more than 200 indoor / outdoor scenes. This dataset contains synchronized RGB-D frames from both Kinect v2 ...
DIODE (Dense Indoor and Outdoor DEpth) is a dataset that contains diverse high-resolution color images with accurate, dense, far-range depth measurements. It is ...
The dataset contains around 100,000 pairs of color images with precise dense depth maps of resolution 1920 × 1080, and we refer to this dataset as a High- ...