diff --git a/configs/ssd/ssdlite_mobilenet_v1.yml b/configs/ssd/ssdlite_mobilenet_v1.yml
index dea79a13a062cdb326118ed3ab517a0f3d06b775..3624a3f6bdcf4eec860a1264d423a72d68a8773b 100644
--- a/configs/ssd/ssdlite_mobilenet_v1.yml
+++ b/configs/ssd/ssdlite_mobilenet_v1.yml
@@ -22,7 +22,7 @@ SSD:
     score_threshold: 0.01
 
 MobileNet:
-  norm_decay: 0.0
+  conv_decay: 0.00004
   conv_group_scale: 1
   extra_block_filters: [[256, 512], [128, 256], [128, 256], [64, 128]]
   with_extra_blocks: true
diff --git a/ppdet/modeling/backbones/mobilenet.py b/ppdet/modeling/backbones/mobilenet.py
index e275fe1f15de3cbcff597fc4fac801e2b01e1c90..b2a0eb45f783f105f7b226310867147e19257bb4 100644
--- a/ppdet/modeling/backbones/mobilenet.py
+++ b/ppdet/modeling/backbones/mobilenet.py
@@ -34,6 +34,7 @@ class MobileNet(object):
     Args:
         norm_type (str): normalization type, 'bn' and 'sync_bn' are supported
         norm_decay (float): weight decay for normalization layer weights
+        conv_decay (float): weight decay for convolution layer weights.
         conv_group_scale (int): scaling factor for convolution groups
         with_extra_blocks (bool): if extra blocks should be added
         extra_block_filters (list): number of filter for each extra block
@@ -43,6 +44,7 @@ class MobileNet(object):
     def __init__(self,
                  norm_type='bn',
                  norm_decay=0.,
+                 conv_decay=0.,
                  conv_group_scale=1,
                  conv_learning_rate=1.0,
                  with_extra_blocks=False,
@@ -51,6 +53,7 @@ class MobileNet(object):
                  weight_prefix_name=''):
         self.norm_type = norm_type
         self.norm_decay = norm_decay
+        self.conv_decay = conv_decay
         self.conv_group_scale = conv_group_scale
         self.conv_learning_rate = conv_learning_rate
         self.with_extra_blocks = with_extra_blocks
@@ -70,6 +73,7 @@ class MobileNet(object):
         parameter_attr = ParamAttr(
             learning_rate=self.conv_learning_rate,
             initializer=fluid.initializer.MSRA(),
+            regularizer=L2Decay(self.conv_decay),
             name=name + "_weights")
         conv = fluid.layers.conv2d(
             input=input,
@@ -139,6 +143,7 @@ class MobileNet(object):
             stride=1,
             num_groups=int(num_groups),
             padding=0,
+            act='relu6',
             name=name + "_extra1")
         normal_conv = self._conv_norm(
             input=pointwise_conv,
@@ -147,6 +152,7 @@ class MobileNet(object):
             stride=2,
             num_groups=int(num_groups),
             padding=1,
+            act='relu6',
             name=name + "_extra2")
         return normal_conv