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المنصة
الرئيسية
SOTA
تصنيف السحابة النقطية ثلاثية الأبعاد بقليل من العينات
Few Shot 3D Point Cloud Classification On 1
Few Shot 3D Point Cloud Classification On 1
المقاييس
Overall Accuracy
Standard Deviation
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
Overall Accuracy
Standard Deviation
Paper Title
ReCon++
98.0
2.3
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
PointGPT
98.0
1.9
PointGPT: Auto-regressively Generative Pre-training from Point Clouds
3D-JEPA
97.6
2.0
3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning
PCP-MAE
97.4
2.3
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
Point-JEPA
97.4
2.2
Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud
Point-LGMask
97.4
2.0
Point-LGMask: Local and Global Contexts Embedding for Point Cloud Pre-training with Multi-Ratio Masking
ReCon
97.3
1.9
Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
Point-RAE
97.3
1.6
Regress Before Construct: Regress Autoencoder for Point Cloud Self-supervised Learning
IDPT
97.3
-
Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models
OTMae3D
97.2
2.3
-
I2P-MAE
97.0
1.8
Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders
point2vec
97.0
2.8
Point2Vec for Self-Supervised Representation Learning on Point Clouds
ACT
96.8
2.3
Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
Point-M2AE
96.8
1.8
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
Point-MAE
96.3
2.5
Masked Autoencoders for Point Cloud Self-supervised Learning
MaskPoint
95.0
3.7
Masked Discrimination for Self-Supervised Learning on Point Clouds
Point-BERT
94.6
3.1
Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling
CrossMoCo
93.8
4.5
CrossMoCo: Multi-modal Momentum Contrastive Learning for Point Cloud
OcCo+DGCNN
90.6
2.8
Unsupervised Point Cloud Pre-Training via Occlusion Completion
OcCo+PointNet
89.7
1.9
Unsupervised Point Cloud Pre-Training via Occlusion Completion
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Few Shot 3D Point Cloud Classification On 1 | SOTA | HyperAI