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HyperAI超神経

3D Object Detection On Kitti Cars Easy

評価指標

AP

評価結果

このベンチマークにおける各モデルのパフォーマンス結果

モデル名
AP
Paper TitleRepository
TRTConv91.90 %--
SA-SSD+EBM91.05%Accurate 3D Object Detection using Energy-Based Models
PV-RCNN++90.14%PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection
RoarNet83.71%RoarNet: A Robust 3D Object Detection based on RegiOn Approximation Refinement-
PC-RGNN89.13%PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection-
STD86.61%STD: Sparse-to-Dense 3D Object Detector for Point Cloud-
F-ConvNet85.88%Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection
PGD19.05%Probabilistic and Geometric Depth: Detecting Objects in Perspective
3D Dual-Fusion91.01%3D Dual-Fusion: Dual-Domain Dual-Query Camera-LiDAR Fusion for 3D Object Detection
GLENet-VR91.67%GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation
AVOD + Feature Pyramid81.94%Joint 3D Proposal Generation and Object Detection from View Aggregation
PointRCNN84.32%PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud
SVGA-Net87.33%SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds-
Frustum PointNets81.2%Frustum PointNets for 3D Object Detection from RGB-D Data
PV-RCNN90.25%PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
SE-SSD91.49%SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud
PC-CNN-V284.33%A General Pipeline for 3D Detection of Vehicles-
Joint87.74%Joint 3D Instance Segmentation and Object Detection for Autonomous Driving-
PointRGCN85.97%--
M3DeTR90.28%M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers
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