DIODE: A Dense Indoor and Outdoor DEpth Dataset

Igor Vasiljevic; Nick Kolkin; Shanyi Zhang; Ruotian Luo; Haochen Wang; Falcon Z. Dai; Andrea F. Daniele; Mohammadreza Mostajabi; Steven Basart; Matthew R. Walter; Gregory Shakhnarovich

DIODE: A Dense Indoor and Outdoor DEpth Dataset

Computer Vision and Pattern Recognition 2019-08-30 v2

Authors: Igor Vasiljevic , Nick Kolkin , Shanyi Zhang , Ruotian Luo , Haochen Wang , Falcon Z. Dai , Andrea F. Daniele , Mohammadreza Mostajabi , Steven Basart , Matthew R. Walter , Gregory Shakhnarovich

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Abstract

We introduce DIODE, a dataset that contains thousands of diverse high resolution color images with accurate, dense, long-range depth measurements. DIODE (Dense Indoor/Outdoor DEpth) is the first public dataset to include RGBD images of indoor and outdoor scenes obtained with one sensor suite. This is in contrast to existing datasets that focus on just one domain/scene type and employ different sensors, making generalization across domains difficult. The dataset is available for download at http://diode-dataset.org

Keywords

image processing

Cite

@article{arxiv.1908.00463,
  title  = {DIODE: A Dense Indoor and Outdoor DEpth Dataset},
  author = {Igor Vasiljevic and Nick Kolkin and Shanyi Zhang and Ruotian Luo and Haochen Wang and Falcon Z. Dai and Andrea F. Daniele and Mohammadreza Mostajabi and Steven Basart and Matthew R. Walter and Gregory Shakhnarovich},
  journal= {arXiv preprint arXiv:1908.00463},
  year   = {2019}
}

DIODE: A Dense Indoor and Outdoor DEpth Dataset

Abstract

Keywords

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