diff --git a/src/lerobot/datasets/lerobot_dataset.py b/src/lerobot/datasets/lerobot_dataset.py
index ec419d557f..3565527337 100644
--- a/src/lerobot/datasets/lerobot_dataset.py
+++ b/src/lerobot/datasets/lerobot_dataset.py
@@ -66,6 +66,7 @@
     write_tasks,
 )
 from lerobot.datasets.video_utils import (
+    VideoEncodingManager,
     VideoFrame,
     concatenate_video_files,
     decode_video_frames,
@@ -1136,8 +1137,9 @@ def save_episode(self, episode_data: dict | None = None) -> None:
         use_batched_encoding = self.batch_encoding_size > 1
 
         if has_video_keys and not use_batched_encoding:
-            for video_key in self.meta.video_keys:
-                ep_metadata.update(self._save_episode_video(video_key, episode_index))
+            with VideoEncodingManager(self):
+                for video_key in self.meta.video_keys:
+                    ep_metadata.update(self._save_episode_video(video_key, episode_index))
 
         # `meta.save_episode` need to be executed after encoding the videos
         self.meta.save_episode(episode_index, episode_length, episode_tasks, ep_stats, ep_metadata)
@@ -1148,7 +1150,8 @@ def save_episode(self, episode_data: dict | None = None) -> None:
             if self.episodes_since_last_encoding == self.batch_encoding_size:
                 start_ep = self.num_episodes - self.batch_encoding_size
                 end_ep = self.num_episodes
-                self._batch_save_episode_video(start_ep, end_ep)
+                with VideoEncodingManager(self):
+                    self._batch_save_episode_video(start_ep, end_ep)
                 self.episodes_since_last_encoding = 0
 
         if not episode_data:
diff --git a/tests/datasets/test_datasets.py b/tests/datasets/test_datasets.py
index e174c57896..a71ec5e6a7 100644
--- a/tests/datasets/test_datasets.py
+++ b/tests/datasets/test_datasets.py
@@ -68,6 +68,19 @@ def image_dataset(tmp_path, empty_lerobot_dataset_factory):
     return empty_lerobot_dataset_factory(root=tmp_path / "test", features=features)
 
 
+@pytest.fixture
+def video_dataset(tmp_path, empty_lerobot_dataset_factory):
+    features = {
+        "image": {
+            "dtype": "video",
+            "shape": DUMMY_HWC,
+            "names": ["height", "width", "channels"],
+            "info": None,
+        }
+    }
+    return empty_lerobot_dataset_factory(root=tmp_path / "test", features=features)
+
+
 def test_same_attributes_defined(tmp_path, lerobot_dataset_factory):
     """
     Instantiate a LeRobotDataset both ways with '__init__()' and 'create()' and verify that instantiated
@@ -344,6 +357,17 @@ def test_add_frame_image_pil(image_dataset):
     assert dataset[0]["image"].shape == torch.Size(DUMMY_CHW)
 
 
+def test_add_frame_video(video_dataset):
+    dataset = video_dataset
+    image = np.random.randint(0, 256, DUMMY_HWC, dtype=np.uint8)
+    dataset.add_frame({"image": Image.fromarray(image)}, task="Dummy task")
+    dataset.save_episode()
+
+    assert dataset[0]["image"].shape == torch.Size(DUMMY_CHW)
+    assert len([str(f) for f in (dataset.root / "videos").glob("**/*.mp4")]) == 1
+    assert not (dataset.root / "images").exists()
+
+
 def test_image_array_to_pil_image_wrong_range_float_0_255():
     image = np.random.rand(*DUMMY_HWC) * 255
     with pytest.raises(ValueError):