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Unsupervised 3D Point Cloud Linear Evaluation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Training a linear classifier(e.g. SVM) on the representations learned in an unsupervised manner on the pretrained(e.g. ShapeNet) dataset.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Unsupervised Point Cloud Pre-Training via Occlusion Completion
Self-supervised Learning of Point Clouds via Orientation Estimation
Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space
SO-Net: Self-Organizing Network for Point Cloud Analysis
FoldingNet: Point Cloud Auto-encoder via Deep Grid Deformation
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.