OpenMMLab Detection Toolbox and Benchmark
https://mmdetection.readthedocs.io/
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| README.md | ||
| metafile.yml | ||
| tridentnet_r50_caffe_1x_coco.py | ||
| tridentnet_r50_caffe_mstrain_1x_coco.py | ||
| tridentnet_r50_caffe_mstrain_3x_coco.py | ||
README.md
Scale-Aware Trident Networks for Object Detection
Introduction
@InProceedings{li2019scale,
title={Scale-Aware Trident Networks for Object Detection},
author={Li, Yanghao and Chen, Yuntao and Wang, Naiyan and Zhang, Zhaoxiang},
journal={The International Conference on Computer Vision (ICCV)},
year={2019}
}
Results and models
We reports the test results using only one branch for inference.
| Backbone | Style | mstrain | Lr schd | Mem (GB) | Inf time (fps) | box AP | Download |
|---|---|---|---|---|---|---|---|
| R-50 | caffe | N | 1x | 37.7 | model | log | ||
| R-50 | caffe | Y | 1x | 37.6 | model | log | ||
| R-50 | caffe | Y | 3x | 40.3 | model | log |
Note
Similar to Detectron2, we haven't implemented the Scale-aware Training Scheme in section 4.2 of the paper.