diff --git a/core/nbv_dataset.py b/core/nbv_dataset.py
index 4573bb0..a3c5e1f 100644
--- a/core/nbv_dataset.py
+++ b/core/nbv_dataset.py
@@ -124,63 +124,20 @@ class NBVReconstructionDataset(BaseDataset):
             scanned_n_to_world_pose,
             scanned_target_pts_num,
         ) = ([], [], [], [])
-        target_pts_num_dict = DataLoadUtil.load_target_pts_num_dict(
-            self.root_dir, scene_name
-        )
         for view in scanned_views:
             frame_idx = view[0]
             coverage_rate = view[1]
             view_path = DataLoadUtil.get_path(self.root_dir, scene_name, frame_idx)
             cam_info = DataLoadUtil.load_cam_info(view_path, binocular=True)
-            target_pts_num = target_pts_num_dict[frame_idx]
-            n_to_world_pose = cam_info["cam_to_world"]
-            nR_to_world_pose = cam_info["cam_to_world_R"]
-
-            if self.load_from_preprocess:
-                downsampled_target_point_cloud = (
-                    DataLoadUtil.load_from_preprocessed_pts(view_path)
-                )
-            else:
-                cached_data = None
-                if self.cache:
-                    cached_data = self.load_from_cache(scene_name, frame_idx)
-
-                if cached_data is None:
-                    print("load depth")
-                    depth_L, depth_R = DataLoadUtil.load_depth(
-                        view_path,
-                        cam_info["near_plane"],
-                        cam_info["far_plane"],
-                        binocular=True,
-                    )
-                    point_cloud_L = DataLoadUtil.get_point_cloud(
-                        depth_L, cam_info["cam_intrinsic"], n_to_world_pose
-                    )["points_world"]
-                    point_cloud_R = DataLoadUtil.get_point_cloud(
-                        depth_R, cam_info["cam_intrinsic"], nR_to_world_pose
-                    )["points_world"]
-
-                    point_cloud_L = PtsUtil.random_downsample_point_cloud(
-                        point_cloud_L, 65536
-                    )
-                    point_cloud_R = PtsUtil.random_downsample_point_cloud(
-                        point_cloud_R, 65536
-                    )
-                    overlap_points = PtsUtil.get_overlapping_points(
-                        point_cloud_L, point_cloud_R
-                    )
-                    downsampled_target_point_cloud = (
-                        PtsUtil.random_downsample_point_cloud(
-                            overlap_points, self.pts_num
-                        )
-                    )
-                    if self.cache:
-                        self.save_to_cache(
-                            scene_name, frame_idx, downsampled_target_point_cloud
-                        )
-                else:
-                    downsampled_target_point_cloud = cached_data
-
+            
+            n_to_world_pose = cam_info["cam_to_world"]  
+            target_point_cloud = (
+                DataLoadUtil.load_from_preprocessed_pts(view_path)
+            )
+            target_pts_num = target_point_cloud.shape[0]
+            downsampled_target_point_cloud = PtsUtil.random_downsample_point_cloud(
+                target_point_cloud, self.pts_num
+            )
             scanned_views_pts.append(downsampled_target_point_cloud)
             scanned_coverages_rate.append(coverage_rate)
             n_to_world_6d = PoseUtil.matrix_to_rotation_6d_numpy(
diff --git a/utils/data_load.py b/utils/data_load.py
index ed5a144..4ec8936 100644
--- a/utils/data_load.py
+++ b/utils/data_load.py
@@ -237,7 +237,7 @@ class DataLoadUtil:
     @staticmethod
     def load_from_preprocessed_pts(path):
         npy_path = os.path.join(
-            os.path.dirname(path), "points", os.path.basename(path) + ".npy"
+            os.path.dirname(path), "pts", os.path.basename(path) + ".npy"
         )
         pts = np.load(npy_path)
         return pts