diff --git a/mmdet/datasets/pipelines/transforms.py b/mmdet/datasets/pipelines/transforms.py
index 0a1b38911..c3c6a56f3 100644
--- a/mmdet/datasets/pipelines/transforms.py
+++ b/mmdet/datasets/pipelines/transforms.py
@@ -2802,6 +2802,7 @@ class CopyPaste:
         self.bbox_occluded_thr = bbox_occluded_thr
         self.mask_occluded_thr = mask_occluded_thr
         self.selected = selected
+        self.paste_by_box = False
 
     def get_indexes(self, dataset):
         """Call function to collect indexes.s.
@@ -2813,6 +2814,42 @@ class CopyPaste:
         """
         return random.randint(0, len(dataset))
 
+    def gen_masks_from_bboxes(self, bboxes, img_shape):
+        """Generate gt_masks based on gt_bboxes.
+
+        Args:
+            bboxes (list): The bboxes's list.
+            img_shape (tuple): The shape of image.
+        Returns:
+            BitmapMasks
+        """
+        self.paste_by_box = True
+        img_h, img_w = img_shape[:2]
+        xmin, ymin = bboxes[:, 0:1], bboxes[:, 1:2]
+        xmax, ymax = bboxes[:, 2:3], bboxes[:, 3:4]
+        gt_masks = np.zeros((len(bboxes), img_h, img_w), dtype=np.uint8)
+        for i in range(len(bboxes)):
+            gt_masks[i,
+                     int(ymin[i]):int(ymax[i]),
+                     int(xmin[i]):int(xmax[i])] = 1
+        return BitmapMasks(gt_masks, img_h, img_w)
+
+    def get_gt_masks(self, results):
+        """Get gt_masks originally or generated based on bboxes.
+
+        If gt_masks is not contained in results,
+        it will be generated based on gt_bboxes.
+        Args:
+            results (dict): Result dict.
+        Returns:
+            BitmapMasks: gt_masks, originally or generated based on bboxes.
+        """
+        if results.get('gt_masks', None) is not None:
+            return results['gt_masks']
+        else:
+            return self.gen_masks_from_bboxes(
+                results.get('gt_bboxes', []), results['img'].shape)
+
     def __call__(self, results):
         """Call function to make a copy-paste of image.
 
@@ -2826,6 +2863,13 @@ class CopyPaste:
         num_images = len(results['mix_results'])
         assert num_images == 1, \
             f'CopyPaste only supports processing 2 images, got {num_images}'
+
+        # Get gt_masks originally or generated based on bboxes.
+        results['gt_masks'] = self.get_gt_masks(results)
+        # only one mix picture
+        results['mix_results'][0]['gt_masks'] = self.get_gt_masks(
+            results['mix_results'][0])
+
         if self.selected:
             selected_results = self._select_object(results['mix_results'][0])
         else:
@@ -2871,6 +2915,8 @@ class CopyPaste:
         src_masks = src_results['gt_masks']
 
         if len(src_bboxes) == 0:
+            if self.paste_by_box:
+                dst_results.pop('gt_masks')
             return dst_results
 
         # update masks and generate bboxes from updated masks
@@ -2899,8 +2945,11 @@ class CopyPaste:
         dst_results['img'] = img
         dst_results['gt_bboxes'] = bboxes
         dst_results['gt_labels'] = labels
-        dst_results['gt_masks'] = BitmapMasks(masks, masks.shape[1],
-                                              masks.shape[2])
+        if self.paste_by_box:
+            dst_results.pop('gt_masks')
+        else:
+            dst_results['gt_masks'] = BitmapMasks(masks, masks.shape[1],
+                                                  masks.shape[2])
 
         return dst_results
 
diff --git a/tests/test_data/test_pipelines/test_transform/test_transform.py b/tests/test_data/test_pipelines/test_transform/test_transform.py
index 8bc1cbb31..1ebc4f369 100644
--- a/tests/test_data/test_pipelines/test_transform/test_transform.py
+++ b/tests/test_data/test_pipelines/test_transform/test_transform.py
@@ -1099,3 +1099,20 @@ def test_copypaste():
     src_results['gt_masks'] = src_masks[valid_inds]
     results['mix_results'] = [copy.deepcopy(src_results)]
     copypaste_module(results)
+    # test copy_paste based on bbox
+    dst_results.pop('gt_masks')
+    src_results.pop('gt_masks')
+    dst_bboxes = dst_results['gt_bboxes']
+    src_bboxes = src_results['gt_bboxes']
+    dst_masks = create_full_masks(dst_bboxes, w, h)
+    src_masks = create_full_masks(src_bboxes, w, h)
+    results = copy.deepcopy(dst_results)
+    results['mix_results'] = [copy.deepcopy(src_results)]
+    results = copypaste_module(results)
+    result_masks = create_full_masks(results['gt_bboxes'], w, h)
+    result_masks_np = np.where(result_masks.to_ndarray().sum(0) > 0, 1, 0)
+    masks_np = np.where(
+        (src_masks.to_ndarray().sum(0) + dst_masks.to_ndarray().sum(0)) > 0, 1,
+        0)
+    assert np.all(result_masks_np == masks_np)
+    assert 'gt_masks' not in results