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Second: Sparsely embedded convolutional detection

Introduction

We implement SECOND and provide the results and checkpoints on KITTI dataset.

@article{yan2018second,
  title={Second: Sparsely embedded convolutional detection},
  author={Yan, Yan and Mao, Yuxing and Li, Bo},
  journal={Sensors},
  year={2018},
  publisher={Multidisciplinary Digital Publishing Institute}
}

Results

KITTI

Backbone Class Lr schd Mem (GB) Inf time (fps) mAP Download
SECFPN Car cyclic 80e 5.4 79.07 model | log
SECFPN 3 Class cyclic 80e 5.4 64.41 model | log

Waymo

Backbone Load Interval Class Lr schd Mem (GB) Inf time (fps) mAP@L1 mAPH@L1 mAP@L2 mAPH@L2 Download
SECFPN 5 3 Class 2x 8.12 65.3 61.7 58.9 55.7 log
above @ Car 2x 8.12 67.1 66.6 58.7 58.2
above @ Pedestrian 2x 8.12 68.1 59.1 59.5 51.5
above @ Cyclist 2x 8.12 60.7 59.5 58.4 57.3

Note: See more details about metrics and data split on Waymo HERE. For implementation details, we basically follow the original settings. All of these results are achieved without bells-and-whistles, e.g. ensemble, multi-scale training and test augmentation.