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Few Shot 3D Point Cloud Classification On 1

评估指标

Overall Accuracy
Standard Deviation

评测结果

各个模型在此基准测试上的表现结果

模型名称
Overall Accuracy
Standard Deviation
Paper TitleRepository
PCP-MAE97.42.3PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
DGCNN31.69.0Dynamic Graph CNN for Learning on Point Clouds
I2P-MAE97.01.8Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders
ReCon++98.02.3ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
MaskPoint95.03.7Masked Discrimination for Self-Supervised Learning on Point Clouds
GPr-Net + Euc (1024)74.42.0GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning
Point-MAE96.32.5Masked Autoencoders for Point Cloud Self-supervised Learning
PointGPT98.01.9PointGPT: Auto-regressively Generative Pre-training from Point Clouds
ReCon97.31.9Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
ACT96.82.3Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
PointNet++38.5316.0PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
Point-M2AE96.81.8Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
OcCo+DGCNN90.62.8Unsupervised Point Cloud Pre-Training via Occlusion Completion
OcCo+PointNet89.71.9Unsupervised Point Cloud Pre-Training via Occlusion Completion
PointCNN65.418.9PointCNN: Convolution On $mathcal{X}$-Transformed Points
SSFSL+PointNet63.210.7Self-Supervised Few-Shot Learning on Point Clouds
GPr-Net + Hyp (512)81.11.5GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning
Point-JEPA97.42.2Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud-
GPr-Net + Hyp (1024)80.40.5GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning
Point-BERT94.63.1Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling
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