16 datasets found

ScaleRAFT: Cross-Scale Recurrent All-Pairs Field Transforms for 3D Motion Estimation

A benchmark for optical flow estimation.

Optical flow estimation on edge devices while ensuring high accuracy.

Unsupervised optical flow benchmark datasets

The dataset used for training and testing the proposed EDNet model for efficient disparity estimation.

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

KITTI 2015 dataset contains videos in 200 street scenes captured by RGB cameras, with sparse depth ground truths captured by Velodyne laser scanner.

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

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...

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

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...