diff --git a/configs/neuralangelo-colmap.yaml b/configs/neuralangelo-colmap.yaml
index 297a3f7..84cfa68 100644
--- a/configs/neuralangelo-colmap.yaml
+++ b/configs/neuralangelo-colmap.yaml
@@ -193,7 +193,7 @@ trainer:
   max_steps: 1e5
   log_every_n_steps: 500
   num_sanity_val_steps: 0
-  val_check_interval: 1e5
+  val_check_interval: 5e4
   limit_train_batches: 1.0
   limit_val_batches: 4
   enable_progress_bar: true
diff --git a/configs/neus-colmap.yaml b/configs/neus-colmap.yaml
index f5dc63c..95804c1 100644
--- a/configs/neus-colmap.yaml
+++ b/configs/neus-colmap.yaml
@@ -191,7 +191,7 @@ trainer:
   max_steps: 1e5
   log_every_n_steps: 500
   num_sanity_val_steps: 0
-  val_check_interval: 1e5
+  val_check_interval: 5e4
   limit_train_batches: 1.0
   limit_val_batches: 4
   enable_progress_bar: true
diff --git a/datasets/colmap.py b/datasets/colmap.py
index 4cd9cf6..2b18aa7 100644
--- a/datasets/colmap.py
+++ b/datasets/colmap.py
@@ -246,10 +246,10 @@ def setup(self, config, split):
                         mask = TF.to_tensor(mask)[0]
                     else:
                         mask = torch.ones_like(img[...,0], device=img.device)
-                        vis_mask = torch.ones_like(img[...,0], device=img.device)
+                    vis_mask = torch.ones_like(img[...,0], device=img.device)
                     all_fg_masks.append(mask) # (h, w)
+                    all_vis_masks.append(vis_mask) # (h, w)
                     all_images.append(img)
-                    all_vis_masks.append(vis_mask)
                     if self.apply_depth:
                         # load estimated or recorded depth map
                         depth_path = os.path.join(self.config.root_dir, f"{frame['depth_path']}")
@@ -271,7 +271,7 @@ def setup(self, config, split):
                         all_depths.append(torch.zeros_like(img[...,0], device=img.device))
                         all_depth_masks.append(torch.zeros_like(img[...,0], device=img.device))
             
-            all_c2w, all_images, all_fg_masks, all_depths, all_depth_masks, self.all_vis_masks = \
+            all_c2w, all_images, all_fg_masks, all_depths, all_depth_masks, all_vis_masks = \
                 torch.stack(all_c2w, dim=0).float(), \
                 torch.stack(all_images, dim=0).float(), \
                 torch.stack(all_fg_masks, dim=0).float(), \
@@ -298,6 +298,7 @@ def setup(self, config, split):
                 'all_fg_masks': all_fg_masks,
                 'all_depths': all_depths,
                 'all_depth_masks': all_depth_masks,
+                'all_vis_masks': all_vis_masks,
             }
 
             ColmapDatasetBase.initialized = True
@@ -309,6 +310,7 @@ def setup(self, config, split):
             self.all_c2w = create_spheric_poses(self.all_c2w[:,:,3], n_steps=self.config.n_test_traj_steps)
             self.all_images = torch.zeros((self.config.n_test_traj_steps, self.h, self.w, 3), dtype=torch.float32)
             self.all_fg_masks = torch.zeros((self.config.n_test_traj_steps, self.h, self.w), dtype=torch.float32)
+            self.all_vis_masks = torch.ones((self.config.n_test_traj_steps, self.h, self.w), dtype=torch.float32)
 
         """
         # for debug use
@@ -342,6 +344,7 @@ def setup(self, config, split):
         if self.config.load_data_on_gpu:
             self.all_images = self.all_images.to(self.rank) 
             self.all_fg_masks = self.all_fg_masks.to(self.rank)
+            self.all_vis_masks = self.all_vis_masks.to(self.rank)
         
 
 class ColmapDataset(Dataset, ColmapDatasetBase):
diff --git a/requirements.txt b/requirements.txt
index 6f4631e..4b688f7 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,4 +1,6 @@
 pytorch-lightning<2
+torchvision
+torchtyping
 omegaconf==2.2.3
 nerfacc==0.3.3
 matplotlib