SOTAVerified

3D Classification

Papers

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Showing 1–50 of 79 papers

TitleStatusHype
PointNeXt: Revisiting PointNet++ with Improved Training and Scaling StrategiesCode3
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world LearningCode2
ULIP: Learning a Unified Representation of Language, Images, and Point Clouds for 3D UnderstandingCode2
ULIP-2: Towards Scalable Multimodal Pre-training for 3D UnderstandingCode2
AXIAL: Attention-based eXplainability for Interpretable Alzheimer's Localized Diagnosis using 2D CNNs on 3D MRI brain scansCode2
OpenShape: Scaling Up 3D Shape Representation Towards Open-World UnderstandingCode2
Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation FeaturesCode1
Weight Excitation: Built-in Attention Mechanisms in Convolutional Neural NetworksCode1
PointHop++: A Lightweight Learning Model on Point Sets for 3D ClassificationCode1
PointNet with KAN versus PointNet with MLP for 3D Classification and Segmentation of Point SetsCode1
Learning Inner-Group Relations on Point CloudsCode1
Learning SO(3) Equivariant Representations with Spherical CNNsCode1
APP-Net: Auxiliary-point-based Push and Pull Operations for Efficient Point Cloud ClassificationCode1
Deep manifold learning reveals hidden dynamics of proteasome autoregulationCode1
MeshWalker: Deep Mesh Understanding by Random WalksCode1
Convolution in the Cloud: Learning Deformable Kernels in 3D Graph Convolution Networks for Point Cloud AnalysisCode1
MVTN: Learning Multi-View Transformations for 3D UnderstandingCode1
Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D RepresentationCode1
Subdivision-Based Mesh Convolution NetworksCode1
Task-Oriented Feature DistillationCode1
MVTN: Multi-View Transformation Network for 3D Shape RecognitionCode1
M3T: Three-Dimensional Medical Image Classifier Using Multi-Plane and Multi-Slice TransformerCode1
Peritumoral Expansion Radiomics for Improved Lung Cancer ClassificationCode1
Multimodal Semi-Supervised Learning for 3D ObjectsCode1
ViT-Lens: Initiating Omni-Modal Exploration through 3D InsightsCode1
Voint Cloud: Multi-View Point Cloud Representation for 3D UnderstandingCode1
Dynamics-aware Adversarial Attack of 3D Sparse Convolution NetworkCode0
Virtual imaging trials improved the transparency and reliability of AI systems in COVID-19 imagingCode0
Deep Learning Based Automated COVID-19 Classification from Computed Tomography ImagesCode0
P3P: Pseudo-3D Pre-training for Scaling 3D Voxel-based Masked AutoencodersCode0
PointACL:Adversarial Contrastive Learning for Robust Point Clouds Representation under Adversarial AttackCode0
SE3D: A Framework For Saliency Method Evaluation In 3D ImagingCode0
Convolutional neural networks for Alzheimer’s disease detection on MRI imagesCode0
SimpleView++: Neighborhood Views for Point Cloud ClassificationCode0
Dynamic Local Geometry Capture in 3D PointCloud ClassificationCode0
Local Neighborhood Features for 3D ClassificationCode0
Triangle-Net: Towards Robustness in Point Cloud LearningCode0
Enhancing Learnability of classification algorithms using simple data preprocessing in fMRI scans of Alzheimer's diseaseCode0
Robustifying Point Cloud Networks by RefocusingCode0
Group Multi-View Transformer for 3D Shape Analysis with Spatial EncodingCode0
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning ModelsCode0
Improving 3D Semi-supervised Learning by Effectively Utilizing All Unlabelled DataCode0
MVIP -- A Dataset and Methods for Application Oriented Multi-View and Multi-Modal Industrial Part Recognition—0
3D Object Classification via Spherical Projections—0
Improved Cryo-EM Pose Estimation and 3D Classification through Latent-Space Disentanglement—0
Adapter-X: A Novel General Parameter-Efficient Fine-Tuning Framework for Vision—0
Advancements in Point Cloud Data Augmentation for Deep Learning: A Survey—0
Advancing Smart Malnutrition Monitoring: A Multi-Modal Learning Approach for Vital Health Parameter Estimation—0
Automated Classification of Body MRI Sequence Type Using Convolutional Neural Networks—0
Automatic Aortic Valve Pathology Detection from 3-Chamber Cine MRI with Spatio-Temporal Attention Maps—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1U-10 ModelAUC0.85—Unverified
2BIMCV-V2 ModelAUC0.68—Unverified