Citation
Ching, Jiun Yen and Wong, Lai Kuan and Kung, Fabian Wai Lee (2022) Multi-View Semantic Scene Completion from A Single Depth Image. In: Postgraduate Colloquium December 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)
Text
CHING JIUN YEN-foe.pdf - Submitted Version Restricted to Repository staff only Download (280kB) |
Abstract
Semantic scene completion aims to jointly predict the complete geometry and categories of objects in a scene, given sparse input from single observation. Previous works have used either depth only or together with 2D-to-3D projected RGB features learned by a 2D segmentation network, all stemming from a single view. We introduce a novel input, a modified flipped truncated signed distance to encode both visible and occluded surface information, simulating the benefits of having multiple views at virtually no extra memory cost. To train a network to produce this input, we derive a new ground truth (GT) from existing 3D instance data. Our experiments show that the novel input produce promising results.
Item Type: | Conference or Workshop Item (Poster) |
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Uncontrolled Keywords: | Segmentation network, Image segmentation |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics |
Divisions: | Faculty of Engineering (FOE) |
Depositing User: | Ms Rosnani Abd Wahab |
Date Deposited: | 28 Dec 2022 01:32 |
Last Modified: | 28 Dec 2022 01:32 |
URII: | http://shdl.mmu.edu.my/id/eprint/11020 |
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