diff --git a/dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50.yml b/dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50.yml
index 3719f6d02ac0c3b81eda5f2e13c5abc48cdf919c..630b9aa09d9eee6aa10b532c097a15500a5ba6d4 100644
--- a/dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50.yml
+++ b/dygraph/configs/faster_rcnn/_base_/faster_rcnn_r50.yml
@@ -34,7 +34,7 @@ RPNHead:
     nms_thresh: 0.7
     pre_nms_top_n: 12000
     post_nms_top_n: 2000
-    topk_after_collect: True
+    topk_after_collect: False
   test_proposal:
     min_size: 0.0
     nms_thresh: 0.7
diff --git a/dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50.yml b/dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50.yml
index 9a6942c9e89390f2ba0df7083dae31dbb8ed0efd..e2043cf673e418c2a68bb74096f69ed18ec3be82 100644
--- a/dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50.yml
+++ b/dygraph/configs/mask_rcnn/_base_/mask_rcnn_r50.yml
@@ -35,7 +35,7 @@ RPNHead:
     nms_thresh: 0.7
     pre_nms_top_n: 12000
     post_nms_top_n: 2000
-    topk_after_collect: True
+    topk_after_collect: False
   test_proposal:
     min_size: 0.0
     nms_thresh: 0.7
diff --git a/dygraph/ppdet/modeling/backbones/resnet.py b/dygraph/ppdet/modeling/backbones/resnet.py
index 86a3c9b963581b27b0a702980b88fbb3e7662784..e59f1761464a59538b692e5413292577175b2be9 100755
--- a/dygraph/ppdet/modeling/backbones/resnet.py
+++ b/dygraph/ppdet/modeling/backbones/resnet.py
@@ -555,7 +555,7 @@ class Res5Head(nn.Layer):
     def out_shape(self):
         return [ShapeSpec(
             channels=self.feat_out,
-            stride=32, )]
+            stride=16, )]
 
     def forward(self, roi_feat, stage=0):
         y = self.res5(roi_feat)
diff --git a/dygraph/ppdet/modeling/bbox_utils.py b/dygraph/ppdet/modeling/bbox_utils.py
index a8566140d4e49c44e9f41499aa84b3a1fbdb2c89..9d90831b6fcdcfccae89a0d30a8e3248f00b58bc 100644
--- a/dygraph/ppdet/modeling/bbox_utils.py
+++ b/dygraph/ppdet/modeling/bbox_utils.py
@@ -50,7 +50,7 @@ def delta2bbox(deltas, boxes, weights):
     dy = deltas[:, 1::4] / wy
     dw = deltas[:, 2::4] / ww
     dh = deltas[:, 3::4] / wh
-    # Prevent sending too large values into np.exp()
+    # Prevent sending too large values into paddle.exp()
     dw = paddle.clip(dw, max=clip_scale)
     dh = paddle.clip(dh, max=clip_scale)
 
@@ -64,7 +64,7 @@ def delta2bbox(deltas, boxes, weights):
     pred_boxes.append(pred_ctr_y - 0.5 * pred_h)
     pred_boxes.append(pred_ctr_x + 0.5 * pred_w)
     pred_boxes.append(pred_ctr_y + 0.5 * pred_h)
-    pred_boxes = paddle.concat(pred_boxes, axis=-1)
+    pred_boxes = paddle.stack(pred_boxes, axis=-1)
 
     return pred_boxes
 
diff --git a/dygraph/ppdet/modeling/heads/bbox_head.py b/dygraph/ppdet/modeling/heads/bbox_head.py
index 3ad260e3ebc5d5caa331248dea0a9320935f8542..9a604e287cbe8c264453cc830dac2d7175b0d955 100644
--- a/dygraph/ppdet/modeling/heads/bbox_head.py
+++ b/dygraph/ppdet/modeling/heads/bbox_head.py
@@ -128,7 +128,7 @@ class BBoxHead(nn.Layer):
     def forward(self, body_feats=None, rois=None, rois_num=None, inputs=None):
         """
         body_feats (list[Tensor]): Feature maps from backbone
-        rois (Tensor): RoIs generated from RPN module
+        rois (list[Tensor]): RoIs generated from RPN module
         rois_num (Tensor): The number of RoIs in each image
         inputs (dict{Tensor}): The ground-truth of image
         """
diff --git a/dygraph/ppdet/modeling/heads/cascade_head.py b/dygraph/ppdet/modeling/heads/cascade_head.py
index 2ef88a3dcca3a1587ac4d38a12525dead531c82f..f1a33e1173d5bf6c284fccbdc1cb3a57987190f7 100644
--- a/dygraph/ppdet/modeling/heads/cascade_head.py
+++ b/dygraph/ppdet/modeling/heads/cascade_head.py
@@ -187,6 +187,7 @@ class CascadeHead(BBoxHead):
         pred_proposals = paddle.concat(proposals) if len(
             proposals) > 1 else proposals[0]
         pred_bbox = delta2bbox(deltas, pred_proposals, weights)
+        pred_bbox = paddle.reshape(pred_bbox, [-1, deltas.shape[-1]])
         num_prop = [p.shape[0] for p in proposals]
         return pred_bbox.split(num_prop)
 
diff --git a/dygraph/ppdet/modeling/proposal_generator/rpn_head.py b/dygraph/ppdet/modeling/proposal_generator/rpn_head.py
index 426d33bf28f44aac87044b8cdc5f69c28059f4d2..6a1c980a452f0390b6e7355210cfc190ceab184a 100644
--- a/dygraph/ppdet/modeling/proposal_generator/rpn_head.py
+++ b/dygraph/ppdet/modeling/proposal_generator/rpn_head.py
@@ -116,7 +116,6 @@ class RPNHead(nn.Layer):
 
         rois, rois_num = self._gen_proposal(scores, deltas, anchors, inputs,
                                             batch_size)
-
         if self.training:
             loss = self.get_loss(scores, deltas, anchors, inputs)
             return rois, rois_num, loss
diff --git a/dygraph/ppdet/py_op/post_process.py b/dygraph/ppdet/py_op/post_process.py
index 41d366787fe6468404b08a24c5ec0c5fef4163b9..04fabaa31001942290495e28e90b3a924b58dd7a 100755
--- a/dygraph/ppdet/py_op/post_process.py
+++ b/dygraph/ppdet/py_op/post_process.py
@@ -55,6 +55,8 @@ def get_seg_res(masks, bboxes, mask_nums, image_id, label_to_cat_id_map):
             score = float(bboxes[k][1])
             label = int(bboxes[k][0])
             k = k + 1
+            if label == -1:
+                continue
             cat_id = label_to_cat_id_map[label]
             rle = mask_util.encode(
                 np.array(