Papers with Code 아카이브

3D Classification

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/AlonLahav/MeshWalker

공식 코드

MeshWalker: Deep Mesh Understanding by Random Walks

https://github.com/AlphaCryo4D/AlphaCryo4D

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Deep manifold learning reveals hidden dynamics of proteasome autoregulation

https://github.com/AnTao97/LGM

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Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network

https://github.com/AutoAILab/M2CP-Learning

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Multimodal Semi-Supervised Learning for 3D Objects

https://github.com/Duplums/yAwareContrastiveLearning

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Contrastive Learning with Continuous Proxy Meta-Data for 3D MRI Classification

https://github.com/GabrieleLozupone/AXIAL

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AXIAL: Attention-based eXplainability for Interpretable Alzheimer's Localized Diagnosis using 2D CNNs on 3D MRI brain scans

https://github.com/IDU-CVLab/COV19D

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Deep Learning Based Automated COVID-19 Classification from Computed Tomography Images

https://github.com/Information-Fusion-Lab-Umass/alzheimers-cnn-study

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Alzheimer's Disease Brain MRI Classification: Challenges and Insights

https://github.com/LifeBeyondExpectations/PointMixer

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PointMixer: MLP-Mixer for Point Cloud Understanding

https://github.com/Microsoft/O-CNN

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O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis

https://github.com/RosettaWYzhang/AdaPC

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On Automatic Data Augmentation for 3D Point Cloud Classification

https://github.com/ShunChengWu/3DSSG

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SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

https://github.com/ShunChengWu/SceneGraphFusion

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SceneGraphFusion: Incremental 3D Scene Graph Prediction from RGB-D Sequences

https://github.com/TencentARC/ViT-Lens

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ViT-Lens: Initiating Omni-Modal Exploration through 3D Insights

https://github.com/VimsLab/Local3DFeatures

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Local Neighborhood Features for 3D Classification

https://github.com/aHapBean/PCP-MAE

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PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders

https://github.com/ajhamdi/MVTN

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MVTN: Multi-View Transformation Network for 3D Shape Recognition

https://github.com/ajhamdi/mvtorch

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MVTN: Learning Multi-View Transformations for 3D Understanding

https://github.com/ajhamdi/vointcloud

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Voint Cloud: Multi-View Point Cloud Representation for 3D Understanding

https://github.com/ali-stanford/pointnet_kan_graphic

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PointNet with KAN versus PointNet with MLP for 3D Classification and Segmentation of Point Sets

https://github.com/baaivision/uni3d

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Uni3D: Exploring Unified 3D Representation at Scale

https://github.com/bigdata-graph/gmvit

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Group Multi-View Transformer for 3D Shape Analysis with Spatial Encoding

https://github.com/cscvlab/InSphereNet

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InSphereNet: a Concise Representation and Classification Method for 3D Object

https://github.com/dagrawa2/gdnn_code

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Densely Connected $G$-invariant Deep Neural Networks with Signed Permutation Representations

https://github.com/daniilidis-group/spherical-cnn

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Learning SO(3) Equivariant Representations with Spherical CNNs

https://github.com/dingxin-zhang/PaRot

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PaRot: Patch-Wise Rotation-Invariant Network via Feature Disentanglement and Pose Restoration

https://github.com/dkoguciuk/ensemble_learning_for_point_clouds

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3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models

https://github.com/dogyoonlee/RSMix-official

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Regularization Strategy for Point Cloud via Rigidly Mixed Sample

https://github.com/engelnico/point-transformer

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Point Transformer

https://github.com/fitushar/AI-in-Lung-Health-Benchmarking-Detection-and-Diagnostic-Models-Across-Multiple-CT-Scan-Datasets

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Peritumoral Expansion Radiomics for Improved Lung Cancer Classification

https://github.com/fitushar/CVIT_ReviCOVID19

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Virtual imaging trials improved the transparency and reliability of AI systems in COVID-19 imaging

https://github.com/fitushar/WeaklySupervised-3D-Classification-of-Chest-CT-using-Aggregated-MultiResolution-Segmentation-Feature

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Weakly Supervised 3D Classification of Chest CT using Aggregated Multi-Resolution Deep Segmentation Features

https://github.com/gfmei/softclu

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Data Augmentation-free Unsupervised Learning for 3D Point Cloud Understanding

https://github.com/griegler/octnet

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OctNet: Learning Deep 3D Representations at High Resolutions

https://github.com/guochengqian/pointnext

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PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

https://github.com/hancyran/RPNet

공식 코드

Learning Inner-Group Relations on Point Clouds

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