diff --git a/tests/processor/test_normalize_processor.py b/tests/processor/test_normalize_processor.py
index cd5c75005..e046adb0d 100644
--- a/tests/processor/test_normalize_processor.py
+++ b/tests/processor/test_normalize_processor.py
@@ -1804,13 +1804,15 @@ def test_stats_override_preservation_in_load_state_dict():
                 override_normalizer.stats[key][stat_name], original_stats[key][stat_name]
             ), f"Stats for {key}.{stat_name} should not match original stats"
 
-    # Verify that _tensor_stats are also correctly set to match the override stats
+    # Verify that _tensor_stats values match the override stats
+    # Note: visual stats are reshaped from (C,) to (C,1,1) by _reshape_visual_stats
     expected_tensor_stats = to_tensor(override_stats)
     for key in expected_tensor_stats:
         for stat_name in expected_tensor_stats[key]:
             if isinstance(expected_tensor_stats[key][stat_name], torch.Tensor):
                 torch.testing.assert_close(
-                    override_normalizer._tensor_stats[key][stat_name], expected_tensor_stats[key][stat_name]
+                    override_normalizer._tensor_stats[key][stat_name].squeeze(),
+                    expected_tensor_stats[key][stat_name].squeeze(),
                 )
 
 
@@ -1849,12 +1851,16 @@ def test_stats_without_override_loads_normally():
     # Stats should now match the original stats (normal behavior)
     # Check that all keys and values match
     assert set(new_normalizer.stats.keys()) == set(original_stats.keys())
+    # Note: visual stats are reshaped from (C,) to (C,1,1) by _reshape_visual_stats,
+    # so we squeeze before comparing values.
     for key in original_stats:
         assert set(new_normalizer.stats[key].keys()) == set(original_stats[key].keys())
         for stat_name in original_stats[key]:
-            np.testing.assert_allclose(
-                new_normalizer.stats[key][stat_name], original_stats[key][stat_name], rtol=1e-6, atol=1e-6
-            )
+            actual = new_normalizer.stats[key][stat_name]
+            expected = original_stats[key][stat_name]
+            if hasattr(actual, "squeeze"):
+                actual = actual.squeeze()
+            np.testing.assert_allclose(actual, expected, rtol=1e-6, atol=1e-6)
 
 
 def test_stats_explicit_provided_flag_detection():
@@ -2075,8 +2081,9 @@ def test_stats_reconstruction_after_load_state_dict():
     assert ACTION in new_normalizer.stats
 
     # Check that values are correct (converted back from tensors)
-    np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["mean"], [0.5, 0.5, 0.5])
-    np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["std"], [0.2, 0.2, 0.2])
+    # Note: visual stats are reshaped to (C,1,1), so we squeeze before comparing
+    np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["mean"].squeeze(), [0.5, 0.5, 0.5])
+    np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["std"].squeeze(), [0.2, 0.2, 0.2])
     np.testing.assert_allclose(new_normalizer.stats[OBS_STATE]["min"], [0.0, -1.0])
     np.testing.assert_allclose(new_normalizer.stats[OBS_STATE]["max"], [1.0, 1.0])
     np.testing.assert_allclose(new_normalizer.stats[ACTION]["mean"], [0.0, 0.0])