HyperAI
Home
News
Latest Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
English
HyperAI
Toggle sidebar
Search the site…
⌘
K
Home
SOTA
3D Point Cloud Linear Classification
3D Point Cloud Linear Classification On
3D Point Cloud Linear Classification On
Metrics
Overall Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Overall Accuracy
Paper Title
Repository
IAE (DGCNN)
92.1
Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning
I2P-MAE
93.4
Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders
AdaCrossNet
91.4
AdaCrossNet: Adaptive Dynamic Loss Weighting for Cross-Modal Contrastive Point Cloud Learning
ReCon
93.4
Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
OcCo
89.2
Unsupervised Point Cloud Pre-Training via Occlusion Completion
CrossPoint
91.2
CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding
MAE-VAE
88.4
Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction
-
Point-M2AE
92.9
Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training
FoldingNet
88.4
FoldingNet: Point Cloud Auto-encoder via Deep Grid Deformation
PointOE
90.7
Self-supervised Learning of Point Clouds via Orientation Estimation
Point-Jigsaw
90.6
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space
-
MID-FC
90.3
Unsupervised 3D Learning for Shape Analysis via Multiresolution Instance Discrimination
SO-Net
87.5
SO-Net: Self-Organizing Network for Point Cloud Analysis
STRL
90.9
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds
PSG-Net
90.9
Progressive Seed Generation Auto-encoder for Unsupervised Point Cloud Learning
-
3D-GAN
83.3
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Point-JEPA
93.7±0.2
Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud
-
ReCon++
93.6
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction
VIP-GAN
90.2
View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions
-
CrossMoCo
91.49
CrossMoCo: Multi-modal Momentum Contrastive Learning for Point Cloud
0 of 20 row(s) selected.
Previous
Next