diff --git a/nerfstudio/exporter/exporter_utils.py b/nerfstudio/exporter/exporter_utils.py
index eb6c5f9b6..9f4168517 100644
--- a/nerfstudio/exporter/exporter_utils.py
+++ b/nerfstudio/exporter/exporter_utils.py
@@ -151,6 +151,10 @@ def generate_point_cloud(
                     CONSOLE.print(f"Please set --normal_output_name to one of: {outputs.keys()}", justify="center")
                     sys.exit(1)
                 normal = outputs[normal_output_name]
+                assert (
+                    torch.min(normal) >= 0.0 and torch.max(normal) <= 1.0
+                ), "Normal values from method output must be in [0, 1]"
+                normal = (normal * 2.0) - 1.0
             point = ray_bundle.origins + ray_bundle.directions * depth
 
             if use_bounding_box:
diff --git a/nerfstudio/models/nerfplayer_nerfacto.py b/nerfstudio/models/nerfplayer_nerfacto.py
index e7ee3d14c..e10b3cad2 100644
--- a/nerfstudio/models/nerfplayer_nerfacto.py
+++ b/nerfstudio/models/nerfplayer_nerfacto.py
@@ -50,6 +50,7 @@ from nerfstudio.model_components.renderers import (
     RGBRenderer,
 )
 from nerfstudio.model_components.scene_colliders import NearFarCollider
+from nerfstudio.model_components.shaders import NormalsShader
 from nerfstudio.models.base_model import Model
 from nerfstudio.models.nerfacto import NerfactoModel, NerfactoModelConfig
 
@@ -162,6 +163,9 @@ class NerfplayerNerfactoModel(NerfactoModel):
         self.renderer_depth = DepthRenderer(method="expected")  # for depth loss
         self.renderer_normals = NormalsRenderer()
 
+        # shaders
+        self.normals_shader = NormalsShader()
+
         # losses
         self.rgb_loss = MSELoss()
 
@@ -192,8 +196,12 @@ class NerfplayerNerfactoModel(NerfactoModel):
         }
 
         if self.config.predict_normals:
-            outputs["normals"] = self.renderer_normals(normals=field_outputs[FieldHeadNames.NORMALS], weights=weights)
-            outputs["pred_normals"] = self.renderer_normals(field_outputs[FieldHeadNames.PRED_NORMALS], weights=weights)
+            outputs["normals"] = self.normals_shader(
+                self.renderer_normals(normals=field_outputs[FieldHeadNames.NORMALS], weights=weights)
+            )
+            outputs["pred_normals"] = self.normals_shader(
+                self.renderer_normals(field_outputs[FieldHeadNames.PRED_NORMALS], weights=weights)
+            )
 
         # These use a lot of GPU memory, so we avoid storing them for eval.
         if self.training: