News: We reimplement the TSD algorithm based on the MMDetection framework.

Paper: TSD(https://arxiv.org/abs/2003.07540) 1st place solutions for openimage 2019 (https://arxiv.org/abs/2003.07557)

The installation of MMDetection can be found from the official github(https://github.com/open-mmlab/mmdetection)

TSD is a plugin detector head which is friendly to any anchor-based two stage detectors (Faster RCNN, Mask RCNN and so on).

V1.0: We firstly reimplement the experiments based on Faster RCNN with Resnet families. The SharedFCBBoxHead is used as the sibling head. The corresponding configuration can be found in (faster_rcnn_r50_fpn_TSD_1x.py, faster_rcnn_r101_fpn_TSD_1x.py, faster_rcnn_r152_fpn_TSD_1x.py)

###Tips:

1. LR can be set to base_lr*total_batch (base_lr=0.00125, 0.04 = 0.00125*32 in our experiments.)
2. An external epoch can be used to perform warmup. (base_lr will be incresed to LR in the first epoch)

Reimplemented methods and backbones are shown in the below table. It's based on the Faster RCNN with FPN. More backbones and experiments are underway.

| Backbone | TSD | AP | AP_0.5 | AP_0.75 | AP_s | AP_m | AP_l | Download | |--------------------|:-----:|:--------------:|:-------:|:--------:|:-------:|:---------:|:--------:| | ResNet50 | | 36.2 | 58.1 | 39.0 | 21.8 | 39.9 |46.1 | | ResNet50 | ✓ | 40.9 | 61.9 | 44.4 | 24.2 | 44.4 |54.0 |model | ResNet101 | | 38.9 | 60.6 | 42.4 | 22.3 | 43.6 |50.6 | | ResNet101 | ✓ | 42.3 | 63.1 | 45.9 | 25.1 | 46.3 |56.5 |model | ResNet152 | | | | | | | | | ResNet152 | ✓ | 43.7 | 64.5 | 47.6 | 26.1 | 48.0 |57.5 |model

Please refer to MMdetection for installation and dataset preparation.

./tools/slurm_train.sh dev TSD configs/faster_rcnn_r152_fpn_TSD_1x.py exp/TSD_r152/ 16

We sinerely appreciate the support of MMDetection for object detection algorithms.

If the TSD helps your research, please cite the follow papers.

@article{song2020revisiting,
  title={Revisiting the Sibling Head in Object Detector},
  author={Song, Guanglu and Liu, Yu and Wang, Xiaogang},
  journal={arXiv preprint arXiv:2003.07540},
  year={2020}
}
@article{liu20201st,
  title={1st Place Solutions for OpenImage2019--Object Detection and Instance Segmentation},
  author={Liu, Yu and Song, Guanglu and Zang, Yuhang and Gao, Yan and Xie, Enze and Yan, Junjie and Loy, Chen Change and Wang, Xiaogang},
  journal={arXiv preprint arXiv:2003.07557},
  year={2020}
}

If you have any questions, please contact (songguanglu@sensetime.com).