diff --git a/nerfstudio/field_components/encodings.py b/nerfstudio/field_components/encodings.py
index 65bff8244b..2e938fa612 100644
--- a/nerfstudio/field_components/encodings.py
+++ b/nerfstudio/field_components/encodings.py
@@ -423,6 +423,13 @@ def get_out_dim(self) -> int:
         return self.num_components * 3
 
     def forward(self, in_tensor: TensorType["bs":..., "input_dim"]) -> TensorType["bs":..., "output_dim"]:
+        """Compute encoding for each position in in_positions
+
+        Args:
+            in_tensor: position inside bounds in range [-1,1],
+
+        Returns: Encoded position
+        """
         plane_coord = torch.stack([in_tensor[..., [0, 1]], in_tensor[..., [0, 2]], in_tensor[..., [1, 2]]])  # [3,...,2]
         line_coord = torch.stack([in_tensor[..., 2], in_tensor[..., 1], in_tensor[..., 0]])  # [3, ...]
         line_coord = torch.stack([torch.zeros_like(line_coord), line_coord], dim=-1)  # [3, ...., 2]
diff --git a/nerfstudio/fields/tensorf_field.py b/nerfstudio/fields/tensorf_field.py
index 6d4e0458be..ac0c242f3d 100644
--- a/nerfstudio/fields/tensorf_field.py
+++ b/nerfstudio/fields/tensorf_field.py
@@ -85,6 +85,7 @@ def __init__(
 
     def get_density(self, ray_samples: RaySamples):
         positions = SceneBox.get_normalized_positions(ray_samples.frustums.get_positions(), self.aabb)
+        positions = positions * 2 - 1
         density = self.density_encoding(positions)
         density_enc = torch.sum(density, dim=-1)[:, :, None]
         relu = torch.nn.ReLU()
@@ -94,6 +95,7 @@ def get_density(self, ray_samples: RaySamples):
     def get_outputs(self, ray_samples: RaySamples, density_embedding: Optional[TensorType] = None) -> TensorType:
         d = ray_samples.frustums.directions
         positions = SceneBox.get_normalized_positions(ray_samples.frustums.get_positions(), self.aabb)
+        positions = positions * 2 - 1
         rgb_features = self.color_encoding(positions)
         rgb_features = self.B(rgb_features)