Hybrid Deep–Geometric Approach for Efficient Consistency Assessment of Stereo Images

We present HGC-Net, a hybrid pipeline for assessing geometric consistency between stereo image pairs. Our method integrates classical epipolar geometry with deep learning components to compute an interpretable scalar score A, reflecting the degree of alignment. Unlike traditional techniques, which m...

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Detalles Bibliográficos

Principais autores:	Michał Kowalczyk, Piotr Napieralski, Dominik Szajerman
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2025-07-01
Series:	Sensors
Assuntos:	stereoscopic images geometric consistency transformer-based object detection semantic inconsistency epipolar geometry stereo vision
Acceso en liña:	https://www.mdpi.com/1424-8220/25/14/4507
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