WALT3D: Generating Realistic Training Data from Time-Lapse Imagery for Reconstructing Dynamic Objects Under Occlusion

Current methods for 2D and 3D object understanding struggle with severe occlusions in busy urban environments, partly due to the lack of large-scale labeled ground-truth annotations for learning occlusion. In this work, we introduce a novel framework for automatically generating a large, realistic d...

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Bibliographic Details
Published in:Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 9514 - 9524
Main Authors: Vuong, Khiem, Reddy, N Dinesh, Tamburo, Robert, Narasimhan, Srinivasa G.
Format: Conference Proceeding
Language:English
Published: IEEE 16.06.2024
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ISSN:1063-6919
Online Access:Get full text
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