Papers with Code · CC BY-SA 4.0

ModelNet40

아카이브 평가 111건 · 마지막 적재/변경 2026-10-30

평가 기록

과거 수집 기록이며 최신 순위가 아닙니다. 데이터셋 버전·split·실험 조건과 지표 방향이 검증되지 않은 결과는 직접 비교할 수 없습니다. 날짜는 논문 날짜이며 최신 평가일을 뜻하지 않습니다.

표가 화면보다 넓으면 좌우로 스크롤하여 논문과 구현 링크를 확인하세요.

원본 기록 순서 · 순위 미부여
모델	원본 지표·값	논문	구현
Point-M2AE	Overall Accuracy 94.0	Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training 2022-05-28	코드 1 · 코드 2 · 코드 3
PointMLS	Overall Accuracy 94.0	ModelNet-O: A Large-Scale Synthetic Dataset for Occlusion-Aware Point Cloud Classification 2024-01-16	코드 1
3D-JEPA	Overall Accuracy 94.0	3D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning 2024-09-24	연결 없음
MKConv	Overall Accuracy 94.0 Number of params 5.63M	MKConv: Multidimensional Feature Representation for Point Cloud Analysis 2021-07-27	연결 없음
SimpleView	Overall Accuracy 93.9 Mean Accuracy 91.8	Revisiting Point Cloud Classification with a Simple and Effective Baseline 2021-01-01	코드 1 · 코드 2
PAConv	Overall Accuracy 93.9	PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds 2021-03-26	코드 1 · 코드 2
SimpleView-DGCNN	Overall Accuracy 93.9	Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline 2021-06-09	코드 1 · 코드 2 · 코드 3
PointMAE+PPT	Overall Accuracy 93.88	Positional Prompt Tuning for Efficient 3D Representation Learning 2024-08-21	코드 1
MVTN	Overall Accuracy 93.8 Mean Accuracy 92.2	MVTN: Multi-View Transformation Network for 3D Shape Recognition 2020-11-26	코드 1 · 코드 2
Feature Geometric Net (FG-Net)	Overall Accuracy 93.8 Mean Accuracy 91.1	FG-Net: Fast Large-Scale LiDAR Point Clouds Understanding Network Leveraging Correlated Feature Mining and Geometric-Aware Modelling 2020-12-17	코드 1
GBNet	Overall Accuracy 93.8 Mean Accuracy 91.0	Geometric Back-projection Network for Point Cloud Classification 2019-11-28	코드 1 · 코드 2
DeltaConv	Overall Accuracy 93.8 Mean class accuracy 91.2	DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds 2021-11-16	코드 1
GDANet	Overall Accuracy 93.8	Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud 2020-12-20	코드 1 · 코드 2 · 코드 3
Point-BERT	Overall Accuracy 93.8	Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling 2021-11-29	코드 1 · 코드 2 · 코드 3
APES (global-based downsample)	Overall Accuracy 93.8	Attention-based Point Cloud Edge Sampling 2023-02-28	코드 1
Point-JEPA (no voting)	Overall Accuracy 93.8±0.2	Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud 2024-04-25	코드 1
Point-PN	Overall Accuracy 93.8 Number of params 0.8M	Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis 2023-03-14	코드 1 · 코드 2 · 코드 3
PointSCNet	Overall Accuracy 93.7 Mean Accuracy 91.4	PointSCNet: Point Cloud Structure and Correlation Learning Based on Space Filling Curve-Guided Sampling 2022-02-21	코드 1
PRA-Net	Overall Accuracy 93.7 Mean Accuracy 91.2	PRA-Net: Point Relation-Aware Network for 3D Point Cloud Analysis 2021-12-09	코드 1
PointTransformer	Overall Accuracy 93.7 Mean Accuracy 90.6	Point Transformer 2020-12-16	코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 · 코드 6 · 코드 7 · 코드 8 · 코드 9 · 코드 10 · 코드 11 · 코드 12 · 코드 13 · 코드 14 · 코드 15 · 코드 16 · 코드 17 · 코드 18 · 코드 19 · 코드 20 · 코드 21 · 코드 22 · 코드 23 · 코드 24
DualMLP	Overall Accuracy 93.7	DualMLP: a two-stream fusion model for 3D point cloud classification 2023-10-10	코드 1
PointMixer	Overall Accuracy 93.6 Mean Accuracy 91.4 Number of params 6.5M	PointMixer: MLP-Mixer for Point Cloud Understanding 2021-11-22	코드 1 · 코드 2 · 코드 3
DeepGCN	Overall Accuracy 93.6 Mean Accuracy 90.9 Number of params 2.2M	DeepGCNs: Making GCNs Go as Deep as CNNs 2019-10-15	코드 1 · 코드 2 · 코드 3 · 코드 4
LCPFormer	Overall Accuracy 93.6 Mean Accuracy 90.7	LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers 2022-10-23	코드 1
DGCNN + SageMix	Overall Accuracy 93.6	SageMix: Saliency-Guided Mixup for Point Clouds 2022-10-13	코드 1
PointVector-S	Overall Accuracy 93.5 Mean Accuracy 91	PointVector: A Vector Representation In Point Cloud Analysis 2022-05-21	코드 1
RSMix	Overall Accuracy 93.5	Regularization Strategy for Point Cloud via Rigidly Mixed Sample 2021-02-03	코드 1
PointConT	Overall Accuracy 93.5	Point Cloud Classification Using Content-based Transformer via Clustering in Feature Space 2023-03-08	코드 1
APES (local-based downsample)	Overall Accuracy 93.5	Attention-based Point Cloud Edge Sampling 2023-02-28	코드 1
DSPoint	Overall Accuracy 93.5 Number of params 1.16M	DSPoint: Dual-scale Point Cloud Recognition with High-frequency Fusion 2021-11-19	코드 1