diff --git a/example/fcn-xs/image_segmentaion.py b/example/fcn-xs/image_segmentaion.py
index 75df2d128a22..562db14d36be 100644
--- a/example/fcn-xs/image_segmentaion.py
+++ b/example/fcn-xs/image_segmentaion.py
@@ -93,8 +93,8 @@ def main():
     model_prefix = "FCN8s_VGG16"
     epoch = 19
 
-    # By default, MXNet will run on the CPU. Uncomment the line below to execute on the GPU
-    # ctx = mx.gpu()
+    # By default, MXNet will run on the CPU. Change to ctx = mx.gpu() to run on GPU.
+    ctx = mx.cpu()
 
     fcnxs, fcnxs_args, fcnxs_auxs = mx.model.load_checkpoint(model_prefix, epoch)
     fcnxs_args["data"] = mx.nd.array(get_data(args.input), ctx)
diff --git a/example/ssd/dataset/pycocotools/coco.py b/example/ssd/dataset/pycocotools/coco.py
index 19a7b8b7f64d..470f086f0b02 100755
--- a/example/ssd/dataset/pycocotools/coco.py
+++ b/example/ssd/dataset/pycocotools/coco.py
@@ -255,22 +255,7 @@ def showAnns(self, anns):
                             color.append(c)
                     else:
                         # mask
-                        t = self.imgs[ann['image_id']]
-                        if type(ann['segmentation']['counts']) == list:
-                            # rle = maskUtils.frPyObjects([ann['segmentation']], t['height'], t['width'])
-                            raise NotImplementedError("maskUtils disabled!")
-                        else:
-                            rle = [ann['segmentation']]
-                        # m = maskUtils.decode(rle)
                         raise NotImplementedError("maskUtils disabled!")
-                        img = np.ones( (m.shape[0], m.shape[1], 3) )
-                        if ann['iscrowd'] == 1:
-                            color_mask = np.array([2.0,166.0,101.0])/255
-                        if ann['iscrowd'] == 0:
-                            color_mask = np.random.random((1, 3)).tolist()[0]
-                        for i in range(3):
-                            img[:,:,i] = color_mask[i]
-                        ax.imshow(np.dstack( (img, m*0.5) ))
                 if 'keypoints' in ann and type(ann['keypoints']) == list:
                     # turn skeleton into zero-based index
                     sks = np.array(self.loadCats(ann['category_id'])[0]['skeleton'])-1
@@ -430,6 +415,4 @@ def annToMask(self, ann):
         :return: binary mask (numpy 2D array)
         """
         rle = self.annToRLE(ann)
-        # m = maskUtils.decode(rle)
         raise NotImplementedError("maskUtils disabled!")
-        return m
diff --git a/example/ssd/symbol/common.py b/example/ssd/symbol/common.py
index 4a0458f87288..a2fb4e69d18c 100644
--- a/example/ssd/symbol/common.py
+++ b/example/ssd/symbol/common.py
@@ -206,6 +206,9 @@ def multibox_layer(from_layers, num_classes, sizes=[.2, .95],
          assert sizes[0] > 0 and sizes[0] < 1
          assert sizes[1] > 0 and sizes[1] < 1 and sizes[1] > sizes[0]
          tmp = np.linspace(sizes[0], sizes[1], num=(len(from_layers)-1))
+         # Ref for start_offset value:
+         # https://arxiv.org/abs/1512.02325
+         start_offset = 0.1
          min_sizes = [start_offset] + tmp.tolist()
          max_sizes = tmp.tolist() + [tmp[-1]+start_offset]
          sizes = zip(min_sizes, max_sizes)