NYUv2 (NYU-Depth V2)

Introduced by Nathan Silberman et al. in Indoor Segmentation and Support Inference from RGBD Images

The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect. It features:

  • 1449 densely labeled pairs of aligned RGB and depth images
  • 464 new scenes taken from 3 cities
  • 407,024 new unlabeled frames
  • Each object is labeled with a class and an instance number. The dataset has several components:
  • Labeled: A subset of the video data accompanied by dense multi-class labels. This data has also been preprocessed to fill in missing depth labels.
  • Raw: The raw RGB, depth and accelerometer data as provided by the Kinect.
  • Toolbox: Useful functions for manipulating the data and labels.
Source: https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html


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