diff --git a/nerfstudio/data/utils/nerfstudio_collate.py b/nerfstudio/data/utils/nerfstudio_collate.py
index c259c46589..8c8a633fb8 100644
--- a/nerfstudio/data/utils/nerfstudio_collate.py
+++ b/nerfstudio/data/utils/nerfstudio_collate.py
@@ -155,6 +155,19 @@ def nerfstudio_collate(batch: Any, extra_mappings: Union[Dict[type, Callable], N
         ), "All cameras must have distortion parameters or none of them should have distortion parameters.\
             Generalized batching will be supported in the future."
 
+        if batch[0].metadata is not None:
+            metadata_keys = batch[0].metadata.keys()
+            assert all(
+                (cam.metadata.keys() == metadata_keys for cam in batch)
+            ), "All cameras must have the same metadata keys."
+        else:
+            assert all((cam.metadata is None for cam in batch)), "All cameras must have the same metadata keys."
+
+        if batch[0].times is not None:
+            assert all((cam.times is not None for cam in batch)), "All cameras must have times present or absent."
+        else:
+            assert all((cam.times is None for cam in batch)), "All cameras must have times present or absent."
+
         # If no batch dimension exists, then we need to stack everything and create a batch dimension on 0th dim
         if elem.shape == ():
             op = torch.stack
@@ -163,11 +176,23 @@ def nerfstudio_collate(batch: Any, extra_mappings: Union[Dict[type, Callable], N
             op = torch.cat
 
         # Create metadata dictionary
-        metadata_keys = batch[0].metadata.keys()
-        assert all(
-            (cam.metadata.keys() == metadata_keys for cam in batch)
-        ), "All cameras must have the same metadata keys."
-        metadata = {key: op([cam.metadata[key] for cam in batch], dim=0) for key in metadata_keys}
+        if batch[0].metadata is not None:
+            metadata = {key: op([cam.metadata[key] for cam in batch], dim=0) for key in batch[0].metadata.keys()}
+        else:
+            metadata = None
+
+        if batch[0].distortion_params is not None:
+            distortion_params = op(
+                [cameras.distortion_params for cameras in batch],
+                dim=0,
+            )
+        else:
+            distortion_params = None
+
+        if batch[0].times is not None:
+            times = torch.stack([cameras.times for cameras in batch], dim=0)
+        else:
+            times = None
 
         return Cameras(
             op([cameras.camera_to_worlds for cameras in batch], dim=0),
@@ -177,20 +202,9 @@ def nerfstudio_collate(batch: Any, extra_mappings: Union[Dict[type, Callable], N
             op([cameras.cy for cameras in batch], dim=0),
             height=op([cameras.height for cameras in batch], dim=0),
             width=op([cameras.width for cameras in batch], dim=0),
-            distortion_params=op(
-                [
-                    cameras.distortion_params
-                    if cameras.distortion_params is not None
-                    else torch.zeros_like(cameras.distortion_params)
-                    for cameras in batch
-                ],
-                dim=0,
-            ),
+            distortion_params=distortion_params,
             camera_type=op([cameras.camera_type for cameras in batch], dim=0),
-            times=torch.stack(
-                [cameras.times if cameras.times is not None else -torch.ones_like(cameras.times) for cameras in batch],
-                dim=0,
-            ),
+            times=times,
             metadata=metadata,
         )