9 datasets found

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

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

Depth estimation is a crucial step for 3D reconstruction with panorama images in recent years. Panorama images maintain the complete spatial information but introduce distortion...

DepthP+P: A method for self-supervised monocular depth estimation using planar and parallax.

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

The dataset used in the paper is the KITTI Vision Benchmark and Cityscapes dataset for monocular depth estimation and structure prediction.

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...