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3D Object Detection On Kitti Cars Hard

评估指标

AP

评测结果

各个模型在此基准测试上的表现结果

模型名称
AP
Paper TitleRepository
SA-SSD+EBM72.78%Accurate 3D Object Detection using Energy-Based Models
Joint74.30%Joint 3D Instance Segmentation and Object Detection for Autonomous Driving-
F-ConvNet68.08%Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection
3D Dual-Fusion79.39%3D Dual-Fusion: Dual-Domain Dual-Query Camera-LiDAR Fusion for 3D Object Detection
PC-RGNN75.54%PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection-
SVGA-Net74.63%SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds-
VoxelNet57.73%VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
TRTConv80.38 %--
PV-RCNN++77.15%PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection
UberATG-MMF68.41%Multi-Task Multi-Sensor Fusion for 3D Object Detection-
PC-CNN-V264.83%A General Pipeline for 3D Detection of Vehicles-
GLENet-VR78.43%GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation
M3DeTR76.96%M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers
Voxel R-CNN77.06Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
PGD9.39%Probabilistic and Geometric Depth: Detecting Objects in Perspective
AVOD + Feature Pyramid66.38%Joint 3D Proposal Generation and Object Detection from View Aggregation
IPOD66.33%IPOD: Intensive Point-based Object Detector for Point Cloud-
Frustum PointNets62.19%Frustum PointNets for 3D Object Detection from RGB-D Data
PV-RCNN76.82%PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection
STD76.06%STD: Sparse-to-Dense 3D Object Detector for Point Cloud-
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