diff --git a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
index fa3dc5ce7..183e7ae8d 100644
--- a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
+++ b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
@@ -80,14 +80,64 @@ class Nerfstudio(DataParser):
         poses = []
         num_skipped_image_filenames = 0
 
+        fx_fixed = "fl_x" in meta
+        fy_fixed = "fl_y" in meta
+        cx_fixed = "cx" in meta
+        cy_fixed = "cy" in meta
+        height_fixed = "h" in meta
+        width_fixed = "w" in meta
+        distort_fixed = False
+        for distort_key in ["k1", "k2", "k3", "p1", "p2"]:
+            if distort_key in meta:
+                distort_fixed = True
+                break
+        fx = []
+        fy = []
+        cx = []
+        cy = []
+        height = []
+        width = []
+        distort = []
+
         for frame in meta["frames"]:
             filepath = PurePath(frame["file_path"])
             fname = self._get_fname(filepath)
             if not fname.exists():
                 num_skipped_image_filenames += 1
-            else:
-                image_filenames.append(fname)
-                poses.append(np.array(frame["transform_matrix"]))
+                continue
+
+            if not fx_fixed:
+                assert "fl_x" in frame, "fx not specified in frame"
+                fx.append(float(frame["fl_x"]))
+            if not fy_fixed:
+                assert "fl_y" in frame, "fy not specified in frame"
+                fy.append(float(frame["fl_y"]))
+            if not cx_fixed:
+                assert "cx" in frame, "cx not specified in frame"
+                cx.append(float(frame["cx"]))
+            if not cy_fixed:
+                assert "cy" in frame, "cy not specified in frame"
+                cy.append(float(frame["cy"]))
+            if not height_fixed:
+                assert "h" in frame, "height not specified in frame"
+                height.append(int(frame["h"]))
+            if not width_fixed:
+                assert "w" in frame, "width not specified in frame"
+                width.append(int(frame["w"]))
+            if not distort_fixed:
+                distort.append(
+                    camera_utils.get_distortion_params(
+                        k1=float(meta["k1"]) if "k1" in meta else 0.0,
+                        k2=float(meta["k2"]) if "k2" in meta else 0.0,
+                        k3=float(meta["k3"]) if "k3" in meta else 0.0,
+                        k4=float(meta["k4"]) if "k4" in meta else 0.0,
+                        p1=float(meta["p1"]) if "p1" in meta else 0.0,
+                        p2=float(meta["p2"]) if "p2" in meta else 0.0,
+                    )
+                )
+
+            image_filenames.append(fname)
+            poses.append(np.array(frame["transform_matrix"]))
             if "mask_path" in frame:
                 mask_filepath = PurePath(frame["mask_path"])
                 mask_fname = self._get_fname(mask_filepath, downsample_folder_prefix="masks_")
@@ -162,23 +212,33 @@ class Nerfstudio(DataParser):
         else:
             camera_type = CameraType.PERSPECTIVE
 
-        distortion_params = camera_utils.get_distortion_params(
-            k1=float(meta["k1"]) if "k1" in meta else 0.0,
-            k2=float(meta["k2"]) if "k2" in meta else 0.0,
-            k3=float(meta["k3"]) if "k3" in meta else 0.0,
-            k4=float(meta["k4"]) if "k4" in meta else 0.0,
-            p1=float(meta["p1"]) if "p1" in meta else 0.0,
-            p2=float(meta["p2"]) if "p2" in meta else 0.0,
-        )
+        idx_tensor = torch.tensor(indices)
+        fx = float(meta["fl_x"]) if fx_fixed else torch.tensor(fx, dtype=torch.float32)[idx_tensor]
+        fy = float(meta["fl_y"]) if fy_fixed else torch.tensor(fy, dtype=torch.float32)[idx_tensor]
+        cx = float(meta["cx"]) if cx_fixed else torch.tensor(cx, dtype=torch.float32)[idx_tensor]
+        cy = float(meta["cy"]) if cy_fixed else torch.tensor(cy, dtype=torch.float32)[idx_tensor]
+        height = int(meta["h"]) if height_fixed else torch.tensor(height, dtype=torch.int32)[idx_tensor]
+        width = int(meta["w"]) if width_fixed else torch.tensor(width, dtype=torch.int32)[idx_tensor]
+        if distort_fixed:
+            distortion_params = camera_utils.get_distortion_params(
+                k1=float(meta["k1"]) if "k1" in meta else 0.0,
+                k2=float(meta["k2"]) if "k2" in meta else 0.0,
+                k3=float(meta["k3"]) if "k3" in meta else 0.0,
+                k4=float(meta["k4"]) if "k4" in meta else 0.0,
+                p1=float(meta["p1"]) if "p1" in meta else 0.0,
+                p2=float(meta["p2"]) if "p2" in meta else 0.0,
+            )
+        else:
+            distortion_params = torch.stack(distort, dim=0)[idx_tensor]
 
         cameras = Cameras(
-            fx=float(meta["fl_x"]),
-            fy=float(meta["fl_y"]),
-            cx=float(meta["cx"]),
-            cy=float(meta["cy"]),
+            fx=fx,
+            fy=fy,
+            cx=cx,
+            cy=cy,
             distortion_params=distortion_params,
-            height=int(meta["h"]),
-            width=int(meta["w"]),
+            height=height,
+            width=width,
             camera_to_worlds=poses[:, :3, :4],
             camera_type=camera_type,
         )