9 datasets found

ETH3D is a small real-world grayscale dataset with both indoor and outdoor scenes. It contains 27 labeled stereo image pairs for training and 20 stereo pairs for testing.

The Middlebury 2014 dataset is a benchmark for stereo matching, consisting of 33 pairs of stereo images with sparse depth ground truth.

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

The KITTI 2012 and 2015 datasets are used for stereo matching experiments.

Large dataset for stereo matching, optical flow, and scene flow estimation

Object scene flow is a dataset for stereo matching and optical flow estimation.

Disparity prediction from stereo images is essential to computer vision applications including autonomous driving, 3D model reconstruction, and object detection.

The dataset used in the paper is the KITTI dataset, which is a benchmark for monocular depth estimation. The dataset consists of a large collection of images and corresponding...

Stereo matching aims to recover the dense reconstruction of unknown scenes by computing the disparity from rectified stereo images, helping robots intelligently interact with...