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3D Object Detection on ScanNet V2 (val)

78.1mAP@0.25ISBNet
68.2270.78573.3575.915Apr 1, 2021Jan 25, 2022Nov 21, 2022Sep 17, 2023Jul 12, 2024May 8, 2025Mar 4, 2026

Evaluation results

MethodLinks
ISBNet2023.0378.162——————————————————————————
MV-DETR2024.087865.8——————————————————————————
V-DETRProtocol=Single Run, TTA=true2023.0877.866——————————————————————————
V-DETR2024.0877.865.9——————————————————————————
V-DETRProtocol=Single Run, TTA=false2023.0877.465——————————————————————————
V-DETRProtocol=Average 25x trials, TTA=true2023.087765.3——————————————————————————
OneFormer3D2023.1176.965.3——————————————————————————
OneFormer3D2024.0876.965.3——————————————————————————
V-DETRProtocol=Average 25x trials, TTA=false2023.0876.864.5——————————————————————————
Swin3D-L+CAGroup3DBackbone=Swin3D-L2024.0876.463.2——————————————————————————
IAELearning Paradigm=Self-supervised, Backbone=CAGroup3D2022.0176.162——————————————————————————
IAEBase Architecture=CAGroup3D, Pre-training Setting=Self-supervised2025.1276.162——————————————————————————
CAGroup3Dmulti-sensor=false2022.1075.161.3——————————————————————————
CAGroup3DProtocol=Single Run2023.0875.161.3——————————————————————————
CAGroup3DLearning Paradigm=Supervised2022.0175.161.3——————————————————————————
CAGroup3DDesign Task=det2023.0975.161.3——————————————————————————
CAGroup3DPresented at=NeurIPS'222023.1175.161.3——————————————————————————
CAGroup3D2024.0875.161.3——————————————————————————
CAGroup3DPre-training Setting=Supervised2025.1275.161.3——————————————————————————
CAGroup3DProtocol=Average 25x trials2023.0874.560.3——————————————————————————
SPGroup3DAggregation=Best2023.1274.359.6——————————————————————————
SPGroup3D2024.0874.359.6——————————————————————————
Mask-Attention-Free TransformerDesign Task=inst2023.0973.563.9——————————————————————————
SPGroup3DAggregation=Average (25 trials)2023.1273.558.3——————————————————————————
CAGroup3D*Presented at=NeurIPS'22, Note=One-stage result from ablation study2023.1273.257.1——————————————————————————
Point-GCCTraining Protocol=Fine-tuning with pre-training, Backbone=TR3D2023.0573.159.6——————————————————————————
Point-GCC+TR3DAugmentation=Point-GCC2024.0873.159.6——————————————————————————
TR3DTraining Protocol=Supervised Only2023.0572.959.3——————————————————————————
TR3DTraining Protocol=Self-supervised Pre-training (Baseline)2023.0572.959.3——————————————————————————
TR3DProtocol=Single Run2023.0872.959.3——————————————————————————
TR3DPresented at=ICIP'232023.1172.959.3——————————————————————————
TR3D2024.0872.959.3——————————————————————————
ORACLEDescription=Upper bound (full annotation), Base detector=CAGroup3D2025.0372.6558.81——————————————————————————
Ours (GroupFree3D)Pre-trained=Yes, Backbone=GroupFree3D2024.1072.355.7——————————————————————————
TR3DProtocol=Average 25x trials2023.087257.4——————————————————————————
TR3DPresent at=ICIP, Paradigm=Fully Supervised2025.037257.4——————————————————————————
Uni3DETRModality=Point Clouds2023.1071.758.3——————————————————————————
SoftGroup2023.0371.659.4——————————————————————————
SoftGroupPresented at=CVPR'222023.1171.659.4——————————————————————————
FCAF3DPresented at=ECCV'22, multi-sensor=false2022.1071.557.3——————————————————————————
FCAF3DTraining Protocol=Supervised Only2023.0571.557.3——————————————————————————
FCAF3DProtocol=Single Run2023.0871.557.3——————————————————————————
FCAF3DLearning Paradigm=Supervised2022.0171.557.3——————————————————————————
FCAF3DDesign Task=det2023.0971.557.3——————————————————————————
FCAF3DModality=Point Clouds2023.1071.557.3——————————————————————————
FCAF3DPresented at=ECCV'222023.1171.557.3——————————————————————————
FCAF3DPresented at=ECCV'22, Aggregation=Best2023.1271.557.3——————————————————————————
FCAF3DPre-training Setting=Supervised2025.1271.557.3——————————————————————————
BrTBackbone=PointNet++w2x, Image Backbone=ViT-B/16, RGB=true2022.1071.355.2——————————————————————————
GroupFree (12, 512) with RepSurf-U²Backbone=RepSurf-U², #Params=23.61M, Infer Speed=195ms2022.0571.254.8——————————————————————————
HyperDet3DPresented at=CVPR 22, multi-sensor=false2022.1070.957.2——————————————————————————
HyperDet3DProtocol=Single Run2023.0870.957.2——————————————————————————
HyperDet3DDesign Task=det2023.0970.957.2——————————————————————————
HyperDet3DModality=Point Clouds2023.1070.957.2——————————————————————————
HyperDet3DPresented at=CVPR 222023.1270.957.2——————————————————————————
TokenFusionPresented at=CVPR 22, multi-sensor=true2022.1070.854.2——————————————————————————
TokenFusionModality=Point Clouds + RGB2023.1070.8———————————————————————————
FCAF3DProtocol=Average 25x trials2023.0870.756——————————————————————————
FCAF3DPresented at=ECCV'22, Aggregation=Average (25 trials)2023.1270.756——————————————————————————
FCAF3DPresent at=ECCV, Paradigm=Fully Supervised2025.0370.756——————————————————————————
RBGNetBackbone=PointNet++w2x, Input modality=Geometric, Number of rays=66, Number of object candidates=512, Result reporting=Best2022.0470.655.2——————————————————————————
RBGNetPresented at=CVPR 22, multi-sensor=false2022.1070.655.2——————————————————————————
RBGNetProtocol=Single Run2023.0870.655.2——————————————————————————
RBGNetDesign Task=det2023.0970.655.2——————————————————————————
RBGNetModality=Point Clouds2023.1070.655.2——————————————————————————
RBGNetPresented at=CVPR 22, Aggregation=Best2023.1270.655.2——————————————————————————
GroupFree (12, 512) with RepSurf-T²Backbone=RepSurf-T², #Params=23.60M, Infer Speed=194ms2022.0570.454.6——————————————————————————
RBGNetBackbone=PointNet++, Input modality=Geometric, Number of rays=66, Number of object candidates=256, Result reporting=Best2022.0470.254.2——————————————————————————
Mask3DDesign Task=inst2023.0970.256.2——————————————————————————
RBGNetBackbone=PointNet++w2x, Input modality=Geometric, Number of rays=66, Number of object candidates=512, Result reporting=Average2022.0469.954.7——————————————————————————
RBGNetProtocol=Average 25x trials2023.0869.954.7——————————————————————————
BrTBackbone=PointNet++, Image Backbone=ViT-S/16, RGB=true2022.1069.753——————————————————————————
RBGNetBackbone=PointNet++, Input modality=Geometric, Number of rays=66, Number of object candidates=256, Result reporting=Average2022.0469.653.6——————————————————————————
RBGNetPresented at=CVPR 22, Aggregation=Average (25 trials)2023.1269.654.7——————————————————————————
GroupFree3D*+DisARMImplementation Platform=MMDetection3D, Layers=L12, Proposals=O512, Width=w2x, Method Enhancement=DisARM2022.0369.353.6——————————————————————————
PBNetPresented at=ICCV'232023.1169.360.1——————————————————————————
Group-Free (24-L) + YOLOSBackbone=PointNet++w2x, RGB=true2022.1069.252.6——————————————————————————
Group-Free-3Dbackbone=PointNet++w2x, decoder depth (L)=12, number of object candidates (O)=5122021.0469.152.8——————————————————————————
Group-Free (L12, O512)backbone=PointNet++w2x, layers=12, object candidates=5122021.0469.152.8————————————————————5.17—————
Group-freeBackbone=PointNet++w2x, Input modality=Geometric, Result reporting=Best2022.0469.152.8——————————————————————————
GroupFree (12, 512)Backbone=PointNet++², #Params=23.60M, Infer Speed=193ms2022.0569.152.8——————————————————————————
Group-FreeBackbone=PointNet++w2x, Layers=24-L, RGB=false2022.1069.152.8——————————————————————————
Group-freePresented at=ICCV'21, multi-sensor=false2022.1069.152.8——————————————————————————
Group-FreeProtocol=Single Run2023.0869.152.8——————————————————————————
GroupFreeLearning Paradigm=Supervised2022.0169.152.8——————————————————————————
Group-freeDesign Task=det2023.0969.152.8——————————————————————————
GroupFreeModality=Point Clouds2023.1069.152.8——————————————————————————
GroupFreePresented at=ICCV'21, Aggregation=Best2023.1269.152.8——————————————————————————
Bridge3D (GroupFree3D)Pre-trained=Yes, Backbone=GroupFree3D2024.1069.151.9——————————————————————————
GroupFreePre-training Setting=Supervised2025.1269.152.8——————————————————————————
GroupFree3D + HPE_MLPMMDetection3D implementation=true2026.0369.153——————————————————————————
GroupFree 6,256BackBone=X-3D, #Param=12.30, GFLOPS=7.12024.046951.1——————————————————————————
GroupFree3D + X-3D2026.036951.1——————————————————————————
Group-Free-3Dbackbone=PointNet++w2x, decoder depth (L)=12, number of object candidates (O)=2562021.0468.852.1——————————————————————————
Group-Free (L12, O256)backbone=PointNet++w2x, layers=12, object candidates=2562021.0468.852.1————————————————————5.23—————
GroupFree (6, 256) with RepSurf-UBackbone=RepSurf-U, #Params=11.50M, Infer Speed=150ms2022.0568.850.5——————————————————————————
GroupFree 6,256BackBone=RepSurf-U, #Param=11.50, GFLOPS=6.82024.0468.850.5——————————————————————————
Group-Free (24-L) + Faster R-CNNBackbone=PointNet++w2x, RGB=true2022.1068.752.2——————————————————————————
Group-freeBackbone=PointNet++w2x, Input modality=Geometric, Result reporting=Average2022.0468.651.8——————————————————————————
Group-FreeProtocol=Average 25x trials2023.0868.651.8——————————————————————————