diff --git a/nerfstudio/model_components/ray_samplers.py b/nerfstudio/model_components/ray_samplers.py
index ef0079ffd..866218ba1 100644
--- a/nerfstudio/model_components/ray_samplers.py
+++ b/nerfstudio/model_components/ray_samplers.py
@@ -393,7 +393,6 @@ class VolumetricSampler(Sampler):
         self.occupancy_grid = occupancy_grid
         if self.scene_aabb is not None:
             self.scene_aabb = self.scene_aabb.to("cuda").flatten()
-        print(self.scene_aabb)
 
     def get_sigma_fn(self, origins, directions) -> Optional[Callable]:
         """Returns a function that returns the density of a point.
diff --git a/nerfstudio/models/nerfacto.py b/nerfstudio/models/nerfacto.py
index 4972dd5be..bf92968da 100644
--- a/nerfstudio/models/nerfacto.py
+++ b/nerfstudio/models/nerfacto.py
@@ -46,7 +46,10 @@ from nerfstudio.model_components.losses import (
     orientation_loss,
     pred_normal_loss,
 )
-from nerfstudio.model_components.ray_samplers import ProposalNetworkSampler
+from nerfstudio.model_components.ray_samplers import (
+    ProposalNetworkSampler,
+    UniformSampler,
+)
 from nerfstudio.model_components.renderers import (
     AccumulationRenderer,
     DepthRenderer,
@@ -95,6 +98,8 @@ class NerfactoModelConfig(ModelConfig):
         ]
     )
     """Arguments for the proposal density fields."""
+    proposal_initial_sampler: Literal["piecewise", "uniform"] = "piecewise"
+    """Initial sampler for the proposal network. Piecewise is preferred for unbounded scenes."""
     interlevel_loss_mult: float = 1.0
     """Proposal loss multiplier."""
     distortion_loss_mult: float = 0.002
@@ -171,12 +176,19 @@ class NerfactoModel(Model):
             1,
             self.config.proposal_update_every,
         )
+
+        # Change proposal network initial sampler if uniform
+        initial_sampler = None  # None is for piecewise as default (see ProposalNetworkSampler)
+        if self.config.proposal_initial_sampler == "uniform":
+            initial_sampler = UniformSampler(single_jitter=self.config.use_single_jitter)
+
         self.proposal_sampler = ProposalNetworkSampler(
             num_nerf_samples_per_ray=self.config.num_nerf_samples_per_ray,
             num_proposal_samples_per_ray=self.config.num_proposal_samples_per_ray,
             num_proposal_network_iterations=self.config.num_proposal_iterations,
             single_jitter=self.config.use_single_jitter,
             update_sched=update_schedule,
+            initial_sampler=initial_sampler,
         )
 
         # Collider
@@ -312,7 +324,6 @@ class NerfactoModel(Model):
     def get_image_metrics_and_images(
         self, outputs: Dict[str, torch.Tensor], batch: Dict[str, torch.Tensor]
     ) -> Tuple[Dict[str, float], Dict[str, torch.Tensor]]:
-
         image = batch["image"].to(self.device)
         rgb = outputs["rgb"]
         acc = colormaps.apply_colormap(outputs["accumulation"])
diff --git a/scripts/benchmarking/launch_train_blender.sh b/scripts/benchmarking/launch_train_blender.sh
index 298e21749..8f7148c03 100644
--- a/scripts/benchmarking/launch_train_blender.sh
+++ b/scripts/benchmarking/launch_train_blender.sh
@@ -28,7 +28,7 @@ fi
 method_opts=()
 if [ "$method_name" = "nerfacto" ]; then
     # https://github.com/nerfstudio-project/nerfstudio/issues/806#issuecomment-1284327844
-    method_opts=(--pipeline.model.background-color white --pipeline.model.near-plane 2. --pipeline.model.far-plane 6. --pipeline.datamanager.camera-optimizer.mode off --pipeline.model.use-average-appearance-embedding False)
+    method_opts=(--pipeline.model.background-color white --pipeline.model.proposal-initial-sampler uniform --pipeline.model.near-plane 2. --pipeline.model.far-plane 6. --pipeline.datamanager.camera-optimizer.mode off --pipeline.model.use-average-appearance-embedding False)
 fi
 
 shift $((OPTIND-1))