SPIDER: Spherical Indoor Depth Renderer

Muhammad Tukur, Giovanni Pintore, Enrico Gobbetti, Jens Schneider, Marco Agus
Proc. Smart Tools and Applications in Graphics (STAG), page 131--138 - october 2022
Download the publication : stag2022-spider.pdf [1.6Mo]  
Today's Extended Reality (XR) applications that call for specific Diminished Reality (DR) strategies to hide specific classes of objects are increasingly using 360â—¦ cameras, which can capture entire areas in a single picture. In this work, we present an interactive-based image editing and rendering system named SPIDER, that takes a spherical 360â—¦ indoor scene as input. The system incorporates the output of deep learning models to abstract the segmentation and depth images of full and empty rooms to allow users to perform interactive exploration and basic editing operations on the reconstructed indoor scene, namely: i) rendering of the scene in various modalities (point cloud, polygonal, wireframe) ii) refurnishing (transferring portions of rooms) iii) deferred shading through the usage of recomputed normal maps. These kinds of scene editing and manipulations can be used for assessing the inference from deep learning models and enable several Mixed Reality (XR) applications in areas such as furniture retails, interior designs, and real estates. Moreover, it can also be useful in data augmentation, arts, designs, and paintings.

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BibTex references

  author       = {Tukur, M. and Pintore, G. and Gobbetti, E. and Schneider, J. and Agus, M.},
  title        = {SPIDER: Spherical Indoor Depth Renderer},
  booktitle    = {Proc. Smart Tools and Applications in Graphics (STAG)},
  pages        = {131--138},
  month        = {october},
  year         = {2022},
  keywords     = {interactive exploration, image-based rendering, indoor reconstruction},
  doi          = {10.2312/stag.20221267},
  url          = {},

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