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Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection
[article]
2021
arXiv
pre-print
We present a flexible and high-performance framework, named Pyramid R-CNN, for two-stage 3D object detection from point clouds. Current approaches generally rely on the points or voxels of interest for RoI feature extraction on the second stage, but cannot effectively handle the sparsity and non-uniform distribution of those points, and this may result in failures in detecting objects that are far away. To resolve the problems, we propose a novel second-stage module, named pyramid RoI head, to
arXiv:2109.02499v1
fatcat:iqbuhwa45zcmxiyaqj72bspm5e