Raster-to-Graph is a novel automatic recognition framework, which achieves structural and semantic recognition of floorplans, addresses the problem of obtaining high-quality vectorized floorplans from ...
Abstract: Graph contrastive learning is usually performed by first conducting Graph Data Augmentation (GDA) and then employing a contrastive learning pipeline to train GNNs. As we know that GDA is an ...
Abstract: Synthetic aperture radar (SAR) imaging provides a distinct advantage in scene understanding due to its capability for all-weather data acquisition. However, in comparison to easily annotated ...
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