SOTAVerified

3D Point Cloud Linear Classification

Training a linear classifier(e.g. SVM) on the embeddings/representations of 3D point clouds. The embeddings/representations are usually trained in an unsupervised manner.

Papers

Showing 2121 of 21 papers

TitleStatusHype
AdaCrossNet: Adaptive Dynamic Loss Weighting for Cross-Modal Contrastive Point Cloud LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1I2P-MAEOverall Accuracy93.4Unverified
2IAE (DGCNN)Overall Accuracy92.1Unverified
3AdaCrossNetOverall Accuracy91.8Unverified
4CrossMoCoOverall Accuracy91.49Unverified
5CrossPointOverall Accuracy91.2Unverified
6STRLOverall Accuracy90.9Unverified
7PSG-NetOverall Accuracy90.9Unverified
8PointOEOverall Accuracy90.7Unverified
9Point-JigsawOverall Accuracy90.6Unverified
10MID-FCOverall Accuracy90.3Unverified
#ModelMetricClaimedVerifiedStatus
1CrossMoCoOverall Accuracy86.06Unverified
2AdaCrossNetOverall Accuracy82.1Unverified
3CrossPointOverall Accuracy81.7Unverified
4OcCoOverall Accuracy78.3Unverified