nyu_depth_v2

  • Description:

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.

Split Examples
'train' 47,584
'validation' 654
  • Features:
FeaturesDict({
    'depth': Tensor(shape=(480, 640), dtype=tf.float16),
    'image': Image(shape=(480, 640, 3), dtype=tf.uint8),
})
@inproceedings{Silberman:ECCV12,
  author    = {Nathan Silberman, Derek Hoiem, Pushmeet Kohli and Rob Fergus},
  title     = {Indoor Segmentation and Support Inference from RGBD Images},
  booktitle = {ECCV},
  year      = {2012}
}
@inproceedings{icra_2019_fastdepth,
  author    = {Wofk, Diana and Ma, Fangchang and Yang, Tien-Ju and Karaman, Sertac and Sze, Vivienne},
  title     = {FastDepth: Fast Monocular Depth Estimation on Embedded Systems},
  booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
  year      = {2019}
}

Visualization