13 datasets found

A benchmark for optical flow estimation.

Optical flow estimation on edge devices while ensuring high accuracy.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors applied their approach to the challenging problem of optical flow estimation and...

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

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

A real-world dataset collected in indoor and outdoor scenarios with sparse optical flow labels.

The dataset used in the paper for unsupervised single image intrinsic decomposition.

Dense pixel matching is required for many computer vision algorithms such as disparity, optical flow or scene flow estimation. Feature Pyramid Networks (FPN) have proven to be a...

The dataset used in the paper is a Sintel dataset, which consists of low-resolution optical flow maps and their corresponding high-resolution RGB images.

Dense pixel matching is required for many computer vision algorithms such as disparity, optical flow or scene flow estimation. Feature Pyramid Networks (FPN) have proven to be a...

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...

The KITTI 2015 dataset is a real-world dataset of street views, containing 200 training stereo image pairs with sparsely labeled disparity from LiDAR data.

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