# Region Proposal by Guided Anchoring ## Introduction We provide config files to reproduce the results in the CVPR 2019 paper for [Region Proposal by Guided Anchoring](https://arxiv.org/abs/1901.03278). ``` @inproceedings{wang2019region, title={Region Proposal by Guided Anchoring}, author={Jiaqi Wang and Kai Chen and Shuo Yang and Chen Change Loy and Dahua Lin}, booktitle={IEEE Conference on Computer Vision and Pattern Recognition}, year={2019} } ``` ## Results and Models The results on COCO 2017 val is shown in the below table. (results on test-dev are usually slightly higher than val). | Method | Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | AR 1000 | Download | | :----: | :-------------: | :-----: | :-----: | :------: | :-----------------: | :------------: | :-----: | :-------------------------------------------------------------------------------------------------------------------------------------------: | | GA-RPN | R-50-FPN | caffe | 1x | 5.0 | 0.55 | 13.3 | 68.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/guided_anchoring/ga_rpn_r50_caffe_fpn_1x_20190513-95e91886.pth) | | GA-RPN | R-101-FPN | caffe | 1x | - | - | - | 69.6 | - | | GA-RPN | X-101-32x4d-FPN | pytorch | 1x | - | - | - | 70.0 | - | | GA-RPN | X-101-64x4d-FPN | pytorch | 1x | - | - | - | 70.5 | - | | Method | Backbone | Style | Lr schd | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download | | :------------: | :-------------: | :-----: | :-----: | :------: | :-----------------: | :------------: | :----: | :-------------------------------------------------------------------------------------------------------------------------------------------------: | | GA-Fast RCNN | R-50-FPN | caffe | 1x | 3.3 | 0.23 | 14.9 | 39.5 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/guided_anchoring/ga_fast_r50_caffe_fpn_1x_20190513-c5af9f8b.pth) | | GA-Faster RCNN | R-50-FPN | caffe | 1x | 5.1 | 0.64 | 9.6 | 39.9 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/guided_anchoring/ga_faster_r50_caffe_fpn_1x_20190513-a52b31fa.pth) | | GA-Faster RCNN | R-101-FPN | caffe | 1x | - | - | - | 41.5 | - | | GA-Faster RCNN | X-101-32x4d-FPN | pytorch | 1x | - | - | - | 42.9 | - | | GA-Faster RCNN | X-101-64x4d-FPN | pytorch | 1x | - | - | - | 43.9 | - | | GA-RetinaNet | R-50-FPN | caffe | 1x | 3.2 | 0.50 | 10.7 | 37.0 | [model](https://s3.ap-northeast-2.amazonaws.com/open-mmlab/mmdetection/models/guided_anchoring/ga_retinanet_r50_caffe_fpn_1x_20190513-29905101.pth) | | GA-RetinaNet | R-101-FPN | caffe | 1x | - | - | - | 38.9 | - | | GA-RetinaNet | X-101-32x4d-FPN | pytorch | 1x | - | - | - | 40.3 | - | | GA-RetinaNet | X-101-64x4d-FPN | pytorch | 1x | - | - | - | 40.8 | - | - In the Guided Anchoring paper, `score_thr` is set to 0.001 in Fast/Faster RCNN and 0.05 in RetinaNet for both baselines and Guided Anchoring.