diff --git a/configs/face_detection/README.md b/configs/face_detection/README.md
index 3f957def6b8919c0b189ae7a2ef849ddec14dfef..a73cf78113f4650bbbef45d9e98a7574665eac93 100644
--- a/configs/face_detection/README.md
+++ b/configs/face_detection/README.md
@@ -87,8 +87,8 @@ optimized network structure.
 | BlazeFace    | Original | 640  |    8    | 32w     | **0.915** | **0.892**  | **0.797** | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_original.tar) |
 | BlazeFace    | Lite     | 640  |    8    | 32w     | 0.909     | 0.885      | 0.781     | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_lite.tar) |
 | BlazeFace    | NAS      | 640  |    8    | 32w     | 0.837     | 0.807      | 0.658     | [model](https://paddlemodels.bj.bcebos.com/object_detection/blazeface_nas.tar) |
-| FaceBoxes    | Original | 640  |    8    | 32w     | 0.875     | 0.848      | 0.568     | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) |
-| FaceBoxes    | Lite     | 640  |    8    | 32w     | 0.898     | 0.872      | 0.752     | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) |
+| FaceBoxes    | Original | 640  |    8    | 32w     | 0.878     | 0.851      | 0.576     | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_original.tar) |
+| FaceBoxes    | Lite     | 640  |    8    | 32w     | 0.901     | 0.875      | 0.760     | [model](https://paddlemodels.bj.bcebos.com/object_detection/faceboxes_lite.tar) |
 
 **NOTES:**  
 - Get mAP in `Easy/Medium/Hard Set` by multi-scale evaluation in `tools/face_eval.py`.
@@ -103,8 +103,8 @@ configs file and set `lite_edition: true`.
 | BlazeFace    | Original | 640  | **0.992**   | **0.762**   |
 | BlazeFace    | Lite     | 640  | 0.990   | 0.756   |
 | BlazeFace    | NAS      | 640  | 0.981   | 0.741   |
-| FaceBoxes    | Original | 640  | 0.985   | 0.731   |
-| FaceBoxes    | Lite     | 640  | 0.987   | 0.741   |
+| FaceBoxes    | Original | 640  | 0.987   | 0.736   |
+| FaceBoxes    | Lite     | 640  | 0.988   | 0.751   |
 
 **NOTES:**  
 - Get mAP by multi-scale evaluation on the FDDB dataset.
diff --git a/ppdet/modeling/architectures/blazeface.py b/ppdet/modeling/architectures/blazeface.py
index 0a02e70ce480b3eac8636f28615a9e3d68209b07..9b292b6a9c79f840aaa17ea896a9ae6eda58b522 100644
--- a/ppdet/modeling/architectures/blazeface.py
+++ b/ppdet/modeling/architectures/blazeface.py
@@ -131,7 +131,8 @@ class BlazeFace(object):
                     fixed_sizes=min_size,
                     fixed_ratios=[1.],
                     clip=False,
-                    offset=0.5)
+                    offset=0.5,
+                    steps=[self.steps[i]] * 2)
             else:
                 box, var = fluid.layers.prior_box(
                     input,
diff --git a/ppdet/modeling/architectures/faceboxes.py b/ppdet/modeling/architectures/faceboxes.py
index ba9d3e09b1dbf418f0b6f036493d1af989a8ce67..0e7c0dec430800ddaa4e6ea28e0cdc502566c8be 100644
--- a/ppdet/modeling/architectures/faceboxes.py
+++ b/ppdet/modeling/architectures/faceboxes.py
@@ -54,7 +54,8 @@ class FaceBoxes(object):
                  output_decoder=SSDOutputDecoder().__dict__,
                  densities=[[4, 2, 1], [1], [1]],
                  fixed_sizes=[[32., 64., 128.], [256.], [512.]],
-                 num_classes=2):
+                 num_classes=2,
+                 steps=[8., 16., 32.]):
         super(FaceBoxes, self).__init__()
         self.backbone = backbone
         self.num_classes = num_classes
@@ -63,6 +64,7 @@ class FaceBoxes(object):
             self.output_decoder = SSDOutputDecoder(**output_decoder)
         self.densities = densities
         self.fixed_sizes = fixed_sizes
+        self.steps = steps
 
     def build(self, feed_vars, mode='train'):
         im = feed_vars['image']
@@ -114,7 +116,8 @@ class FaceBoxes(object):
                 fixed_sizes=fixed_sizes,
                 fixed_ratios=[1.],
                 clip=False,
-                offset=0.5)
+                offset=0.5,
+                steps=[self.steps[i]] * 2)
 
             num_boxes = box.shape[2]