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Journal Articles International Journal of Computer Vision Year : 2021

3D Semantic Scene Completion: a Survey

Abstract

Semantic Scene Completion (SSC) aims to jointly estimate the complete geometry and semantics of a scene, assuming partial sparse input. In the last years following the multiplication of large-scale 3D datasets, SSC has gained significant momentum in the research community because it holds unresolved challenges. Specifically, SSC lies in the ambiguous completion of large unobserved areas and the weak supervision signal of the ground truth. This led to a substantially increasing number of papers on the matter. This survey aims to identify, compare and analyze the techniques providing a critical analysis of the SSC literature on both methods and datasets. Throughout the paper, we provide an in-depth analysis of the existing works covering all choices made by the authors while highlighting the remaining avenues of research. SSC performance of the SoA on the most popular datasets is also evaluated and analyzed.
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Dates and versions

hal-03324932 , version 1 (24-08-2021)

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Luis Roldão, Raoul de Charette, Anne Verroust-Blondet. 3D Semantic Scene Completion: a Survey. International Journal of Computer Vision, 2021, ⟨10.1007/s11263-021-01504-5⟩. ⟨hal-03324932⟩

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