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Chen et al., 2024 - Google Patents

GeoSegNet: point cloud semantic segmentation via geometric encoder–decoder modeling

Chen et al., 2024

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Document ID
10711598542835075364
Author
Chen C
Wang Y
Chen H
Yan X
Ren D
Guo Y
Xie H
Wang F
Wei M
Publication year
Publication venue
The Visual Computer

External Links

Snippet

Semantic segmentation of point clouds, aiming to assign each point a semantic category, is critical to 3D scene understanding. Although significant advances in recent years, most of the existing methods still suffer from either the object-level misclassification or the boundary …
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Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
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