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3D Object Detection On Kitti Cars Hard

Metrics

AP

Results

Performance results of various models on this benchmark

Paper Title
TRTConv80.38 %-
3D Dual-Fusion79.39%3D Dual-Fusion: Dual-Domain Dual-Query Camera-LiDAR Fusion for 3D Object Detection
GLENet-VR78.43%GLENet: Boosting 3D Object Detectors with Generative Label Uncertainty Estimation
PV-RCNN++77.15%PV-RCNN++: Point-Voxel Feature Set Abstraction With Local Vector Representation for 3D Object Detection
SE-SSD77.15%SE-SSD: Self-Ensembling Single-Stage Object Detector From Point Cloud
Voxel R-CNN77.06Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
M3DeTR76.96%M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers
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
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
Joint74.30%Joint 3D Instance Segmentation and Object Detection for Autonomous Driving
CIA-SSD72.87CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud
SA-SSD+EBM72.78%Accurate 3D Object Detection using Energy-Based Models
PointRGCN70.60%PointRGCN: Graph Convolution Networks for 3D Vehicles Detection Refinement
UberATG-MMF68.41%Multi-Task Multi-Sensor Fusion for 3D Object Detection
F-ConvNet68.08%Frustum ConvNet: Sliding Frustums to Aggregate Local Point-Wise Features for Amodal 3D Object Detection
PointRCNN67.86%PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud
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
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3D Object Detection On Kitti Cars Hard | SOTA | HyperAI