diff --git a/src/lerobot/processor/normalize_processor.py b/src/lerobot/processor/normalize_processor.py
index 89b6f1c18..1649b4b31 100644
--- a/src/lerobot/processor/normalize_processor.py
+++ b/src/lerobot/processor/normalize_processor.py
@@ -137,12 +137,21 @@ class _NormalizationMixin:
         self._reshape_visual_stats()
 
     def _reshape_visual_stats(self) -> None:
-        """Reshape visual stats from ``[C]`` to ``[C, 1, 1]`` for image broadcasting."""
+        """Reshape flat ``(C,)`` visual stats to ``(C, 1, 1)`` for image broadcasting.
+
+        No-op for stats from :func:`~lerobot.datasets.compute_stats.compute_stats`
+        (already ``(C, 1, 1)``). Needed by RL training, which can start without
+        a dataset and supplies stats manually via JSON config.
+        """
         for key, feature in self.features.items():
-            if feature.type == FeatureType.VISUAL and key in self._tensor_stats:
-                for stat_name, stat_tensor in self._tensor_stats[key].items():
-                    if isinstance(stat_tensor, Tensor) and stat_tensor.ndim == 1:
-                        self._tensor_stats[key][stat_name] = stat_tensor.reshape(-1, 1, 1)
+            if feature.type != FeatureType.VISUAL:
+                continue
+            if key not in self._tensor_stats:
+                continue
+            for stat_name, stat_tensor in self._tensor_stats[key].items():
+                if not isinstance(stat_tensor, Tensor) or stat_tensor.ndim != 1:
+                    continue
+                self._tensor_stats[key][stat_name] = stat_tensor.reshape(-1, 1, 1)
 
     def to(
         self, device: torch.device | str | None = None, dtype: torch.dtype | None = None