Dataset Restricted Access


Zioulis Nikolaos; Karakottas Antonis; Zarpalas Dimitrios; Daras Petros

A dataset of omnidirectional (360 - spherical panoramas)  images with their corresponding ground truth depths.

The 360 dataset provides 360 color images of indoor scenes along with their corresponding ground truth depth annotations. This dataset is composed from renders of other publicly available textured 3D datasets of indoor scenes. Specifically, it contains renders from two Computer Generated (CG) datasets, SunCG, SceneNet, and two realistic ones, acquired by scanning indoor building, Stanford2D3D, and Matterport3D. The 360 renders are produced by utilizing a path-tracing renderer and placing a spherical camera and a uniform light source at the same position in the scene. 

More information can be found  @


Recent work on depth estimation up to now has only focused on projective images ignoring 360 content which is now increasingly and more easily produced. However, we show that monocular depth estimation models trained on traditional images produce sub-optimal results on omnidirectional images, showcasing the need for training directly on 360 datasets, which however, are hard to acquire. In this work, we circumvent the challenges associated to acquiring high quality 360 datasets with ground truth depth annotations, by re-using recently released large scale 3D datasets and re-purposing them to 360 via rendering. This dataset, which is considerably larger than similar projective datasets, is publicly offered to the community to enable future research in this direction. We use this dataset to learn in an end-to-end fashion the task of depth estimation from 360 images. We show promising results in our synthesized data as well as in unseen realistic images.
Restricted Access

You may request access to the files in this upload, provided that you fulfil the conditions below. The decision whether to grant/deny access is solely under the responsibility of the record owner.

Access to the 360D dataset requires to agree with the terms and conditions for each of the 3D model datasets that were used to create (i.e. render) this  360  color/depth image dataset:

  1. Matterport3D (train & test splits available)
  2. Stanford2D3D / Building Parser (train & test splits available)
  3. SunCG (train & test splits available)
  4. SceneNet (test splits available)

Therefore, in order to grant you access to this dataset, we need you to fill this request form.

After completing this form and requesting access from Zenodo, you will be granted access to this Zenodo repository to download  the 360D dataset.

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