Real-Time 3D Visual Perception by Cross-Dimensional Refined Learning

We introduce a novel learning method that can effectively perceive both the geometry structure and semantic labels of a 3D scene in real time. Existing real-time 3D scene reconstruction approaches often rely on volumetric schemes to regress a Truncated Signed Distance Function (TSDF) as the 3D repre...

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Bibliographic Details
Published in:	IEEE transactions on circuits and systems for video technology Vol. 34; no. 10; pp. 10326 - 10338
Main Authors:	Hong, Ziyang, Patrick Yue, C.
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	3D perception 3D reconstruction 3D semantic segmentation deep learning Feature extraction Image reconstruction Image segmentation Industrial applications Labels Learning Monocular vision Neural networks Real time Real-time systems Semantic segmentation Semantics Sensors Space perception Three-dimensional displays Visual perception
ISSN:	1051-8215, 1558-2205
Online Access:	Get full text
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