SOTAVerified

Unsupervised 3D Point Cloud Linear Evaluation

Training a linear classifier(e.g. SVM) on the representations learned in an unsupervised manner on the pretrained(e.g. ShapeNet) dataset.

Papers

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Showing 1–8 of 8 papers

TitleStatusHype
Spatio-temporal Self-Supervised Representation Learning for 3D Point CloudsCode1
Unsupervised Point Cloud Pre-Training via Occlusion CompletionCode1
Self-supervised Learning of Point Clouds via Orientation EstimationCode1
SO-Net: Self-Organizing Network for Point Cloud AnalysisCode0
FoldingNet: Point Cloud Auto-encoder via Deep Grid DeformationCode0
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial ModelingCode0
Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction—0
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space—0
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