diff --git a/test/test_transforms.py b/test/test_transforms.py
index 01688022b58..6de4be5943e 100644
--- a/test/test_transforms.py
+++ b/test/test_transforms.py
@@ -1670,7 +1670,7 @@ def test_random_crop():
     assert result.size(1) == height + 1
     assert result.size(2) == width + 1
 
-    t = transforms.RandomCrop(48)
+    t = transforms.RandomCrop(33)
     img = torch.ones(3, 32, 32)
     with pytest.raises(ValueError, match=r"Required crop size .+ is larger than input image size .+"):
         t(img)
diff --git a/torchvision/prototype/transforms/_geometry.py b/torchvision/prototype/transforms/_geometry.py
index 79704099d98..301d52df1d7 100644
--- a/torchvision/prototype/transforms/_geometry.py
+++ b/torchvision/prototype/transforms/_geometry.py
@@ -443,7 +443,7 @@ def _get_params(self, sample: Any) -> Dict[str, Any]:
             if height < output_height:
                 height += 2 * (output_height - height)
 
-        if height + 1 < output_height or width + 1 < output_width:
+        if height < output_height or width < output_width:
             raise ValueError(
                 f"Required crop size {(output_height, output_width)} is larger then input image size {(height, width)}"
             )
diff --git a/torchvision/transforms/transforms.py b/torchvision/transforms/transforms.py
index 095460675cc..4076b65dbd6 100644
--- a/torchvision/transforms/transforms.py
+++ b/torchvision/transforms/transforms.py
@@ -628,7 +628,7 @@ def get_params(img: Tensor, output_size: Tuple[int, int]) -> Tuple[int, int, int
         _, h, w = F.get_dimensions(img)
         th, tw = output_size
 
-        if h + 1 < th or w + 1 < tw:
+        if h < th or w < tw:
             raise ValueError(f"Required crop size {(th, tw)} is larger than input image size {(h, w)}")
 
         if w == tw and h == th: