diff --git a/configs/guided_anchoring/README.md b/configs/guided_anchoring/README.md
index 1d8bb009e00da2d088f6c709133a9512026548e6..3821944dd6148e83123982f5a3b7dbec9d4134fe 100644
--- a/configs/guided_anchoring/README.md
+++ b/configs/guided_anchoring/README.md
@@ -17,25 +17,25 @@ We provide config files to reproduce the results in the CVPR 2019 paper for [Reg
 
 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  |                                                                          -                                                                          |
+| 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    |   7.1    |        0.66         |      9.8       |  69.6   | [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_rpn_r101_caffe_fpn_1x_20190523-91e0b817.pth) |
+| GA-RPN | X-101-32x4d-FPN | pytorch |   1x    |   8.5    |        0.88         |      8.5       |  70.0   | [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_rpn_x101_32x4d_fpn_1x_20190523-a60df28c.pth) |
+| GA-RPN | X-101-64x4d-FPN | pytorch |   1x    |   11.4   |        1.24         |      6.5       |  70.5   | [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_rpn_x101_64x4d_fpn_1x_20190523-9f2449ba.pth) |
+
+
+|     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    |   7.3    |        0.75         |      8.0       |  41.5  |  [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_faster_r101_caffe_fpn_1x_20190523-9a711ec5.pth)   |
+| GA-Faster RCNN | X-101-32x4d-FPN | pytorch |   1x    |   8.7    |        0.97         |      7.1       |  42.9  |  [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_faster_x101_32x4d_fpn_1x_20190523-8dc3e59a.pth)   |
+| GA-Faster RCNN | X-101-64x4d-FPN | pytorch |   1x    |   11.6   |        1.33         |      5.7       |  43.9  |  [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_faster_x101_64x4d_fpn_1x_20190523-a8589c97.pth)   |
+|  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    |   5.3    |        0.63         |      8.5       |  38.9  | [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_retinanet_r101_caffe_fpn_1x_20190523-792ad63d.pth) |
+|  GA-RetinaNet  | X-101-32x4d-FPN | pytorch |   1x    |   6.7    |        0.87         |      7.5       |  40.3  | [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_retinanet_x101_32x4d_fpn_1x_20190523-4ec3f13c.pth) |
+|  GA-RetinaNet  | X-101-64x4d-FPN | pytorch |   1x    |   9.6    |        1.22         |      5.8       |  40.8  | [model](https://open-mmlab.s3.ap-northeast-2.amazonaws.com/mmdetection/models/guided_anchoring/ga_retinanet_x101_64x4d_fpn_1x_20190523-013d1913.pth) |
 
 
 
diff --git a/mmdet/models/anchor_heads/guided_anchor_head.py b/mmdet/models/anchor_heads/guided_anchor_head.py
index da43aa811c9494dae675f067a97c2e71c34800b6..0053cf59146e569ac17395f54393efe4b39fd099 100644
--- a/mmdet/models/anchor_heads/guided_anchor_head.py
+++ b/mmdet/models/anchor_heads/guided_anchor_head.py
@@ -114,7 +114,10 @@ class GuidedAnchorHead(AnchorHead):
                                gamma=2.0,
                                alpha=0.25,
                                loss_weight=1.0),
-                 loss_shape=dict(type='IoULoss', beta=0.2, loss_weight=1.0),
+                 loss_shape=dict(type='IoULoss',
+                                 style='bounded',
+                                 beta=0.2,
+                                 loss_weight=1.0),
                  loss_cls=dict(type='CrossEntropyLoss',
                                use_sigmoid=True,
                                loss_weight=1.0),