diff --git a/test/test_backbone_utils.py b/test/test_backbone_utils.py
index 7ee1aed1459..712dccf11a8 100644
--- a/test/test_backbone_utils.py
+++ b/test/test_backbone_utils.py
@@ -1,25 +1,11 @@
-import unittest
-
-
 import torch
 from torchvision.models.detection.backbone_utils import resnet_fpn_backbone
 
+import pytest
 
-class ResnetFPNBackboneTester(unittest.TestCase):
-    @classmethod
-    def setUpClass(cls):
-        cls.dtype = torch.float32
-
-    def test_resnet18_fpn_backbone(self):
-        device = torch.device('cpu')
-        x = torch.rand(1, 3, 300, 300, dtype=self.dtype, device=device)
-        resnet18_fpn = resnet_fpn_backbone(backbone_name='resnet18', pretrained=False)
-        y = resnet18_fpn(x)
-        self.assertEqual(list(y.keys()), ['0', '1', '2', '3', 'pool'])
 
-    def test_resnet50_fpn_backbone(self):
-        device = torch.device('cpu')
-        x = torch.rand(1, 3, 300, 300, dtype=self.dtype, device=device)
-        resnet50_fpn = resnet_fpn_backbone(backbone_name='resnet50', pretrained=False)
-        y = resnet50_fpn(x)
-        self.assertEqual(list(y.keys()), ['0', '1', '2', '3', 'pool'])
+@pytest.mark.parametrize('backbone_name', ('resnet18', 'resnet50'))
+def test_resnet_fpn_backbone(backbone_name):
+    x = torch.rand(1, 3, 300, 300, dtype=torch.float32, device='cpu')
+    y = resnet_fpn_backbone(backbone_name=backbone_name, pretrained=False)(x)
+    assert list(y.keys()) == ['0', '1', '2', '3', 'pool']