diff --git a/test/test_ops.py b/test/test_ops.py
index 86e1c2b0ba7..9eb6342e378 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -548,5 +548,30 @@ def test_frozenbatchnorm2d_repr(self):
         self.assertEqual(t.__repr__(), expected_string)
 
 
+class BoxConversionTester(unittest.TestCase):
+    @staticmethod
+    def _get_box_sequences():
+        # Define here the argument type of `boxes` supported by region pooling operations
+        box_tensor = torch.tensor([[0, 0, 0, 100, 100], [1, 0, 0, 100, 100]], dtype=torch.float)
+        box_list = [torch.tensor([[0, 0, 100, 100]], dtype=torch.float),
+                    torch.tensor([[0, 0, 100, 100]], dtype=torch.float)]
+        box_tuple = tuple(box_list)
+        return box_tensor, box_list, box_tuple
+
+    def test_check_roi_boxes_shape(self):
+        # Ensure common sequences of tensors are supported
+        for box_sequence in self._get_box_sequences():
+            self.assertIsNone(ops._utils.check_roi_boxes_shape(box_sequence))
+
+    def test_convert_boxes_to_roi_format(self):
+        # Ensure common sequences of tensors yield the same result
+        ref_tensor = None
+        for box_sequence in self._get_box_sequences():
+            if ref_tensor is None:
+                ref_tensor = box_sequence
+            else:
+                self.assertTrue(torch.equal(ref_tensor, ops._utils.convert_boxes_to_roi_format(box_sequence)))
+
+
 if __name__ == '__main__':
     unittest.main()
diff --git a/torchvision/ops/_utils.py b/torchvision/ops/_utils.py
index 714022f0421..f514664042b 100644
--- a/torchvision/ops/_utils.py
+++ b/torchvision/ops/_utils.py
@@ -27,7 +27,7 @@ def convert_boxes_to_roi_format(boxes):
 
 
 def check_roi_boxes_shape(boxes):
-    if isinstance(boxes, list):
+    if isinstance(boxes, (list, tuple)):
         for _tensor in boxes:
             assert _tensor.size(1) == 4, \
                 'The shape of the tensor in the boxes list is not correct as List[Tensor[L, 4]]'