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Research map / Point clouds / Segmentation and detection

Associatively Segmenting Instances and Semantics in Point Clouds

CVPR 2019 · Point clouds › Segmentation and detection · approach: Point cloud semantic segmentation · 293 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add semantic awareness to the instance branch (ablation)ASIS with PointNet · S3DIS 6-fold CVmWCov: 46.3 to 47.4Helped
add instance fusion to the semantic branch (ablation)ASIS with PointNet · S3DIS 6-fold CVmIoU: 49.5 to 50.0Helped
add instance fusion to the semantic branch (ablation)ASIS with PointNet · S3DIS 6-fold CVmWCov: 46.3 to 47.0Helped
add semantic awareness and instance fusion together (ablation)ASIS with PointNet · S3DIS 6-fold CVmIoU: 49.5 to 51.1Helped
add semantic awareness and instance fusion together (ablation)ASIS with PointNet · S3DIS 6-fold CVmWCov: 46.3 to 48.2Helped
associate semantic awareness and instance fusion end-to-endASIS with PointNet · S3DIS 6-fold CVmWCov: 46.3 to 48.2Helped
associate semantic awareness and instance fusion end-to-endASIS with PointNet · S3DIS 6-fold CVmIoU: 49.5 to 51.1Helped
use ASIS instead of SGPNPointNet instance segmentation · S3DIS 6-fold CVmWCov: 40.8 to 48.2Helped
use ASIS instead of PointNet (RePr)PointNet semantic segmentation · ShapeNet testmIoU: 83.4 to 84.0Helped
use ASIS instead of PointNet++*PointNet++ semantic segmentation · ShapeNet testmIoU: 84.3 to 85.0Helped
use ASIS rather than SGPNinstance segmentation · S3DIS Area 5inference time: 726 to 205 msHelped

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