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Classification on ScanObjectNN

93.2OARECON + PPT
67.273.9580.787.45May 11, 2022Jan 14, 2023Sep 20, 2023May 26, 2024Jan 30, 2025Oct 6, 2025Jun 12, 2026

Evaluation results

MethodLinks
RECON + PPTBackbone=RECON, #TP (M)=23.22026.0393.2————
RECON#TP (M)=43.6, FLOPs=5.32026.0393.1————
RECON + MCFTBackbone=RECON, #TP (M)=22.7, FLOPs=4.82026.0393.1————
RECON + PointGSTBackbone=RECON, #TP (M)=22.7, FLOPs=4.82026.0392.9————
Point-MAE + PPTBackbone=Point-MAE, #TP (M)=23.4, FLOPs=4.82026.0392.4————
RECON + DAPTBackbone=RECON, #TP (M)=23.2, FLOPs=5.02026.0392.4————
ACT#TP (M)=22.1, FLOPs=4.82026.0391.9————
RECON + IDPTBackbone=RECON, #TP (M)=23.8, FLOPs=7.22026.0391.6————
Point-BERT + MCFTBackbone=Point-BERT, #TP (M)=22.7, FLOPs=4.82026.0391.5————
Point-MAE + MCFTBackbone=Point-MAE, #TP (M)=22.7, FLOPs=4.82026.0390.9————
DeLA + X-3DGFLOPS=1.53, #Params=5.4M2024.0490.789.9———
DeLAGFLOPS=1.50, #Params=5.3M2024.0490.489.3———
Point-MAE + DAPTBackbone=Point-MAE, #TP (M)=23.2, FLOPs=5.02026.0390.2————
Point-MAE + PointGSTBackbone=Point-MAE, #TP (M)=22.7, FLOPs=4.82026.0390.2————
Point-MAE + IDPTBackbone=Point-MAE, #TP (M)=23.8, FLOPs=7.22026.0390————
Point-BERT + DAPTBackbone=Point-BERT, #TP (M)=23.2, FLOPs=5.02026.0389.7————
Point-BERT + PointGSTBackbone=Point-BERT, #TP (M)=22.7, FLOPs=4.82026.0389.7————
MaskPoint#TP (M)=22.12026.0389.3————
PointMetaBase-S + X-3DGFLOPS=0.59, #Params=1.5M2024.0488.8387.16———
Point-M2AE#TP (M)=15.3, FLOPs=3.62026.0388.8————
SPoTr2024.0488.686.8———
Point-MAE#TP (M)=22.1, FLOPs=4.82026.0388.3————
Point-BERT + IDPTBackbone=Point-BERT, #TP (M)=23.8, FLOPs=7.22026.0388.3————
PointNeXt-SGFLOPS=1.64, #Params=1.4M2024.0488.286.84———
PointMetaBase-SGFLOPS=0.55, #Params=1.4M2024.0488.286.9———
PointVector#Params=1.55M2024.0488.1786.69———
Point-BERT#TP (M)=22.1, FLOPs=4.82026.0388.1————
DC-CCNN++2026.0687.784.4———
DC-CCNN2026.0687.384.1———
PointStackmetric_selection=best2022.0587.286.2———
PointStackaggregation=mean2022.0586.985.8———
DGCNN#TP (M)=1.8, FLOPs=2.42026.0386.2————
RepSurf-U (deeper)Input=1k pnts, #Params=6.806M, FLOPs=2.43G, Note=PointNet++ (SSG) with double channels and deeper networks2022.058683.1———
RepSurf-UParams. (M)=6.82022.058683.1———
PointMLPGFLOPS=31.4, #Params=13.2M2024.0485.784.4———
OcCo#TP (M)=22.1, FLOPs=4.82026.0385.5————
PointMLPaggregation=mean2022.0585.483.9———
PointMLP2026.0685.483.9———
Point-MAE2022.0585.2————
RepSurf-U+Input=1k pnts, #Params=1.483M, FLOPs=0.81G, Train Speed=4.08ms, Infer Speed=3.10ms2022.0584.681.9———
RepSurf-T+Input=1k pnts, #Params=1.479M, FLOPs=0.79G, Train Speed=3.33ms, Infer Speed=2.47ms2022.0584.381.6———
RepSurf-UInput=1k pnts, #Params=1.483M, FLOPs=0.81G, Train Speed=4.08ms, Infer Speed=3.10ms2022.0584.381.3———
PointNet++#TP (M)=1.5, FLOPs=1.72026.0384.3————
RepSurf-TInput=1k pnts, #Params=1.479M, FLOPs=0.79G, Train Speed=3.33ms, Infer Speed=2.47ms2022.0584.181.2———
Point-TnT2022.0583.581———
PointBERT2022.0583.1————
MVTNInput=multi-view, #Params=4.24M, FLOPs=1.78G2022.0582.8————
MVTN2022.0582.8————
MVTNGFLOPS=1.78, #Params=4.24M2024.0482.8————
MVTN2026.0682.8————
PRA-Net2022.0582.179.1———
PRANetParams. (M)=2.3, Throughput (ins./sec.)=4932022.0582.179.1———
PRANet2026.0682.179.1———
GBNet2022.0580.577.8———
Simpleview2022.0580.5————
GBNetParams. (M)=8.8, Throughput (ins./sec.)=1942022.0580.577.8———
GBNet2026.0680.577.8———
SimpleView2026.0680.5————
DRNet2022.0580.378———
DRNet2026.0680.378———
BGA-PN++2026.0680.277.5———
BGA-DGCNN2026.0679.775.7———
PointNet#TP (M)=3.5, FLOPs=0.52026.0379.2————
PointCNN2022.0578.575.1———
PointCNNParams. (M)=0.6, Throughput (ins./sec.)=442022.0578.575.1———
DGCNNInput=1k pnts, #Params=1.82M, FLOPs=2.43G2022.0578.173.6———
DGCNN2022.0578.173.6———
DGCNNParams. (M)=1.8, Throughput (ins./sec.)=4022022.0578.173.6———
DGCNNGFLOPS=2.43, #Params=1.82M2024.0478.173.6———
PointNet++ (SSG version)Input=1k pnts, #Params=1.475M, FLOPs=0.77G, Train Speed=2.75ms, Infer Speed=1.98ms2022.0577.975.4———
PointNet++2022.0577.975.4———
PointNet++Params. (M)=1.5, Throughput (ins./sec.)=18722022.0577.975.4———
PointNet++GFLOPS=1.7, #Params=1.5M2024.0477.975.4———
PointNetInput=1k pnts, #Params=3.47M, FLOPs=0.45G, Train Speed=1.76ms, Infer Speed=0.81ms2022.0568.263.4———
PointNet2022.0568.263.4———
PointNetParams. (M)=3.5, Throughput (ins./sec.)=42122022.0568.263.4———
PointNetGFLOPS=0.45, #Params=3.47M2024.0468.263.4———
CLIP2Zero-shot=true2023.03——39.1——
CLIP2Protocol=15-way, Shots=4-S2023.03——51.3——
CLIP2Protocol=15-way, Shots=8-S2023.03——59.6——
CLIP2Protocol=15-way, Shots=16-S2023.03——62.5——
CLIP2Protocol=10-way, Shots=10-S2023.03——60.6——
CLIP2Protocol=10-way, Shots=20-S2023.03——66.3——
Clip2PointZero-shot=true2023.03——23.3——
CrossPointProtocol=10-way, Shots=10-S2023.03——58.7——
CrossPointProtocol=10-way, Shots=20-S2023.03——64.6——
MixCon3DEncoder=SparseConv, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——54.473.983.3
MixCon3DEncoder=PointBERT, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——52.669.778.6
MixCon3D (retrained)Encoder=SparseConv, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——5673.282.8
MixCon3D (retrained)Encoder=PointBERT, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——55.572.881.1
OccTIPEncoder=SparseConv, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——61.778.486.9
OccTIPEncoder=PointBERT, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——60.678.286
OccTIPEncoder=DuoMamba, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——63.581.389.2
OpenAlignEncoder=ViT-H-14, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——59.576.883.7
OpenShapeEncoder=SparseConv, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——52.772.783.6
OpenShapeEncoder=PointBERT, Zero-shot protocol=True, Pre-trained on ShapeNetCore=True2025.02——51.369.478.4
PointCLIPZero-shot=true2023.03——15.4——
PointCLIPProtocol=15-way, Shots=4-S2023.03——46——
PointCLIPProtocol=15-way, Shots=8-S2023.03——50——
PointCLIPProtocol=15-way, Shots=16-S2023.03——55.6——