Occupancy Planes for Single-View RGB-D Human Reconstruction

Xiaoming Zhao, Yuan Ting Hu, Zhongzheng Ren, Alexander G. Schwing

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Single-view RGB-D human reconstruction with implicit functions is often formulated as per-point classification. Specifically, a set of 3D locations within the view-frustum of the camera are first projected independently onto the image and a corresponding feature is subsequently extracted for each 3D location. The feature of each 3D location is then used to classify independently whether the corresponding 3D point is inside or outside the observed object. This procedure leads to sub-optimal results because correlations between predictions for neighboring locations are only taken into account implicitly via the extracted features. For more accurate results we propose the occupancy planes (OPlanes) representation, which enables to formulate single-view RGB-D human reconstruction as occupancy prediction on planes which slice through the camera's view frustum. Such a representation provides more flexibility than voxel grids and enables to better leverage correlations than per-point classification. On the challenging S3D data we observe a simple classifier based on the OPlanes representation to yield compelling results, especially in difficult situations with partial occlusions due to other objects and partial visibility, which haven't been addressed by prior work.

Original languageEnglish (US)
Title of host publicationAAAI-23 Technical Tracks 3
EditorsBrian Williams, Yiling Chen, Jennifer Neville
PublisherAmerican Association for Artificial Intelligence (AAAI) Press
Number of pages9
ISBN (Electronic)9781577358800
StatePublished - Jun 27 2023
Event37th AAAI Conference on Artificial Intelligence, AAAI 2023 - Washington, United States
Duration: Feb 7 2023Feb 14 2023

Publication series

NameProceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023


Conference37th AAAI Conference on Artificial Intelligence, AAAI 2023
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Artificial Intelligence


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