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SPIDER: A framework for processing, editing and presenting immersive high-resolution spherical indoor scenes

journal contribution
submitted on 2024-07-02, 07:27 and posted on 2024-07-02, 07:27 authored by M. Tukur, G. Pintore, E. Gobbetti, J. Schneider, M. Agus

Today’s Extended Reality (XR) applications that call for specific Diminished Reality (DR) strategies to hide specific classes of objects are increasingly using 360° cameras, which can capture entire areas in a single picture. In this work, we present an interactive-based image processing, editing and rendering system named SPIDER, that takes a spherical 360° indoor scene as input. The system is composed of a novel integrated deep learning architecture for extracting geometric and semantic information of full and empty rooms, based on gated and dilated convolutions, followed by a super-resolution module for improving the resolution of the color and depth signals. The obtained high resolution representations 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 precomputed 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 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. We report on the performance improvement of the various processing components on public domain spherical image indoor datasets.

Other Information

Published in: Graphical Models
See article on publisher's website:


Qatar National Research Fund (NPRP14S-0403-210132)

European Commission (813170), Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication.



  • English



Publication Year

  • 2023

License statement

This Item is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU