diff --git a/python/tvm/relay/frontend/onnx.py b/python/tvm/relay/frontend/onnx.py
index 5e72abd65d7b..05e86dbe004b 100644
--- a/python/tvm/relay/frontend/onnx.py
+++ b/python/tvm/relay/frontend/onnx.py
@@ -1988,6 +1988,7 @@ def _impl_v1(cls, inputs, attr, params):
         data = inputs[0]
         input_shape = infer_shape(data)
         ndim = len(input_shape)
+        num_spatial_dims = ndim - 2
         if "auto_pad" in attr:
             attr["auto_pad"] = attr["auto_pad"].decode("utf-8")
             if attr["auto_pad"] in ("SAME_UPPER", "SAME_LOWER"):
@@ -1995,7 +1996,8 @@ def _impl_v1(cls, inputs, attr, params):
                 # one will need to run dynamic_to_static on this model after import
                 data = autopad(
                     data,
-                    attr["strides"],
+                    # this is meant to handle the field 'strides' being optional for opsets 11+
+                    attr.get("strides", [1] * num_spatial_dims),
                     attr["kernel_shape"],
                     [1] * ndim,
                     mode=attr["auto_pad"],
diff --git a/tests/python/frontend/onnx/test_forward.py b/tests/python/frontend/onnx/test_forward.py
index cf5795837cce..517514df7f7a 100644
--- a/tests/python/frontend/onnx/test_forward.py
+++ b/tests/python/frontend/onnx/test_forward.py
@@ -3939,6 +3939,17 @@ def verify_lppool(x_shape, kernel_shape, p, strides, pads, out_shape, auto_pad="
         auto_pad="SAME_UPPER",
     )
 
+    # Pool2D with empty stride
+    verify_lppool(
+        x_shape=[1, 3, 32, 32],
+        kernel_shape=[2, 2],
+        p=4,
+        strides=None,
+        pads=None,
+        out_shape=[1, 3, 32, 32],
+        auto_pad="SAME_LOWER",
+    )
+
     # Pool3D with stride
     verify_lppool(
         x_shape=[1, 1, 32, 32, 32],