Publication | Open Access
AFDet: Anchor Free One Stage 3D Object Detection
96
Citations
30
References
2020
Year
Geometric Modeling3D Computer VisionPoint CloudMachine VisionImage AnalysisEngineeringNatural SciencesObject DetectionField RoboticsAnchor ParametersComputer EngineeringEntire AfdetPoint Cloud ProcessingComputer ScienceMedical Image ComputingComputational Geometry3D Object RecognitionComputer Vision
High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving. Most previous works try to solve it using anchor-based detection methods which come with two drawbacks: post-processing is relatively complex and computationally expensive; tuning anchor parameters is tricky. We are the first to address these drawbacks with an anchor free and Non-Maximum Suppression free one stage detector called AFDet. The entire AFDet can be processed efficiently on a CNN accelerator or a GPU with the simplified post-processing. Without bells and whistles, our proposed AFDet performs competitively with other one stage anchor-based methods on KITTI validation set and Waymo Open Dataset validation set.
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