diff --git a/python/tvm/relay/frontend/keras.py b/python/tvm/relay/frontend/keras.py
index 1913d4a2681a..aba4160695fe 100644
--- a/python/tvm/relay/frontend/keras.py
+++ b/python/tvm/relay/frontend/keras.py
@@ -131,11 +131,13 @@ def _convert_advanced_activation(inexpr, keras_layer, etab, data_layout, input_s
 
     if act_type == "Softmax":
         axis = keras_layer.axis
-        dims = len(input_shape)
+        dims = len(input_shape) if input_shape else 0
         if isinstance(axis, list):
             raise tvm.error.OpAttributeUnImplemented(f"Softmax with axes {axis} is not supported.")
         if data_layout == "NCHW":
-            if axis == -1:
+            if dims == 0:
+                axis = 0
+            elif axis == -1:
                 axis = 1
             else:
                 axis = axis + 1 if axis < dims - 1 else 1
diff --git a/tests/python/frontend/keras/test_forward.py b/tests/python/frontend/keras/test_forward.py
index 50a0e9850559..53e2ca8dbe23 100644
--- a/tests/python/frontend/keras/test_forward.py
+++ b/tests/python/frontend/keras/test_forward.py
@@ -229,6 +229,13 @@ def test_forward_activations(self, keras_mod):
             keras_model = keras_mod.models.Model(data, x)
             verify_keras_frontend(keras_model)
             verify_keras_frontend(keras_model, need_transpose=False, layout="NHWC")
+        # Test the input dimension = 1
+        data = keras_mod.layers.Input(shape=(11,))
+        act_func = keras_mod.layers.Softmax()
+        x = act_func(data)
+        keras_model = keras_mod.models.Model(data, x)
+        verify_keras_frontend(keras_model)
+        verify_keras_frontend(keras_model, need_transpose=False, layout="NHWC")
 
     def test_forward_activations_except(self, keras_mod):
         """