diff --git a/arguments/__init__.py b/arguments/__init__.py
index dfcfea9..8ba03db 100644
--- a/arguments/__init__.py
+++ b/arguments/__init__.py
@@ -134,6 +134,7 @@ class OptimizationParams(ParamGroup):
         self.opacity_threshold_coarse = 0.005
         self.opacity_threshold_fine_init = 0.005
         self.opacity_threshold_fine_after = 0.005
+        self.batch_size=1,
         
         super().__init__(parser, "Optimization Parameters")
 
diff --git a/arguments/dynerf/default.py b/arguments/dynerf/default.py
index 57453fa..29035f7 100644
--- a/arguments/dynerf/default.py
+++ b/arguments/dynerf/default.py
@@ -6,22 +6,24 @@ ModelHiddenParams = dict(
      'resolution': [64, 64, 64, 150]
     },
     multires = [1,2,4,8],
-    defor_depth = 2,
+    defor_depth = 1,
     net_width = 256,
     plane_tv_weight = 0.0002,
     time_smoothness_weight = 0.001,
     l1_time_planes =  0.001,
+    no_do=False
 
 )
 OptimizationParams = dict(
     dataloader=True,
     iterations = 30_000,
+    batch_size=4,
     coarse_iterations = 3000,
-    densify_until_iter = 15_000,
-    opacity_reset_interval = 6000,
+    densify_until_iter = 20_000,
+    opacity_reset_interval = 20000,
 
-    opacity_threshold_coarse = 0.005,
-    opacity_threshold_fine_init = 0.005,
-    opacity_threshold_fine_after = 0.005,
+    opacity_threshold_coarse = 0.05,
+    opacity_threshold_fine_init = 0.05,
+    opacity_threshold_fine_after = 0.05,
     # pruning_interval = 2000
 )
\ No newline at end of file
diff --git a/arguments/dynerf_2/default.py b/arguments/dynerf_2/default.py
new file mode 100644
index 0000000..5428474
--- /dev/null
+++ b/arguments/dynerf_2/default.py
@@ -0,0 +1,29 @@
+ModelHiddenParams = dict(
+    kplanes_config = {
+     'grid_dimensions': 2,
+     'input_coordinate_dim': 4,
+     'output_coordinate_dim': 16,
+     'resolution': [64, 64, 64, 150]
+    },
+    multires = [1,2,4,8],
+    defor_depth = 1,
+    net_width = 256,
+    plane_tv_weight = 0.0002,
+    time_smoothness_weight = 0.001,
+    l1_time_planes =  0.001,
+    no_do=False
+
+)
+OptimizationParams = dict(
+    dataloader=True,
+    iterations = 20_000,
+    batch_size=8,    
+    coarse_iterations = 3000,
+    densify_until_iter = 20_000,
+    opacity_reset_interval = 3000,
+
+    opacity_threshold_coarse = 0.05,
+    opacity_threshold_fine_init = 0.05,
+    opacity_threshold_fine_after = 0.05,
+    # pruning_interval = 2000
+)
\ No newline at end of file
diff --git a/arguments/dynerf_3/default.py b/arguments/dynerf_3/default.py
new file mode 100644
index 0000000..99221a4
--- /dev/null
+++ b/arguments/dynerf_3/default.py
@@ -0,0 +1,29 @@
+ModelHiddenParams = dict(
+    kplanes_config = {
+     'grid_dimensions': 2,
+     'input_coordinate_dim': 4,
+     'output_coordinate_dim': 16,
+     'resolution': [64, 64, 64, 150]
+    },
+    multires = [1,2,4,8],
+    defor_depth = 1,
+    net_width = 256,
+    plane_tv_weight = 0.0002,
+    time_smoothness_weight = 0.001,
+    l1_time_planes =  0.001,
+    no_do=False
+
+)
+OptimizationParams = dict(
+    dataloader=True,
+    iterations = 60_000,
+    batch_size=8,
+    coarse_iterations = 3000,
+    densify_until_iter = 20_000,
+    opacity_reset_interval = 20000,
+
+    opacity_threshold_coarse = 0.05,
+    opacity_threshold_fine_init = 0.05,
+    opacity_threshold_fine_after = 0.05,
+    # pruning_interval = 2000
+)
\ No newline at end of file
diff --git a/arguments/dynerf_4/default.py b/arguments/dynerf_4/default.py
new file mode 100644
index 0000000..bb4c4c6
--- /dev/null
+++ b/arguments/dynerf_4/default.py
@@ -0,0 +1,29 @@
+ModelHiddenParams = dict(
+    kplanes_config = {
+     'grid_dimensions': 2,
+     'input_coordinate_dim': 4,
+     'output_coordinate_dim': 16,
+     'resolution': [64, 64, 64, 150]
+    },
+    multires = [1,2,4,8],
+    defor_depth = 1,
+    net_width = 256,
+    plane_tv_weight = 0.0002,
+    time_smoothness_weight = 0.001,
+    l1_time_planes =  0.001,
+    no_do=False
+
+)
+OptimizationParams = dict(
+    dataloader=True,
+    iterations = 60_000,
+    batch_size=1,
+    coarse_iterations = 3000,
+    densify_until_iter = 40_000,
+    opacity_reset_interval = 20000,
+
+    opacity_threshold_coarse = 0.05,
+    opacity_threshold_fine_init = 0.05,
+    opacity_threshold_fine_after = 0.05,
+    # pruning_interval = 2000
+)
\ No newline at end of file
diff --git a/arguments/dynerf_static/default.py b/arguments/dynerf_static/default.py
new file mode 100644
index 0000000..3762828
--- /dev/null
+++ b/arguments/dynerf_static/default.py
@@ -0,0 +1,34 @@
+ModelHiddenParams = dict(
+    kplanes_config = {
+     'grid_dimensions': 2,
+     'input_coordinate_dim': 4,
+     'output_coordinate_dim': 16,
+     'resolution': [64, 64, 64, 150]
+    },
+    multires = [1,2,4,8],
+    defor_depth = 1,
+    net_width = 256,
+    plane_tv_weight = 0.0002,
+    time_smoothness_weight = 0.001,
+    l1_time_planes =  0.001,
+    no_do=False
+
+)
+OptimizationParams = dict(
+    dataloader=True,
+    iterations = 10_000,
+    batch_size=8,    
+    coarse_iterations = 10000,
+    densify_until_iter = 20_000,
+    opacity_reset_interval = 3000,
+
+    opacity_threshold_coarse = 0.05,
+    opacity_threshold_fine_init = 0.05,
+    opacity_threshold_fine_after = 0.05,
+    # pruning_interval = 2000
+    # deformation_lr_init = 0.00016,
+    # deformation_lr_final = 0.000016,
+    # deformation_lr_delay_mult = 0.01,
+    # grid_lr_init = 0.0016,
+    # grid_lr_final = 0.00016,
+)
\ No newline at end of file
diff --git a/arguments/hypernerf/default.py b/arguments/hypernerf/default.py
index 009e278..7544e38 100644
--- a/arguments/hypernerf/default.py
+++ b/arguments/hypernerf/default.py
@@ -15,9 +15,10 @@ ModelHiddenParams = dict(
 )
 OptimizationParams = dict(
     dataloader=False,
-    iterations = 60_000,
+    iterations = 30000,
+    batch_size=1,
     coarse_iterations = 3000,
-    densify_until_iter = 45_000,
+    densify_until_iter = 20_000,
     opacity_reset_interval = 6000,
     # position_lr_init = 0.00016,
     # position_lr_final = 0.0000016,
diff --git a/scene/grid.py b/scene/grid.py
new file mode 100644
index 0000000..42272ee
--- /dev/null
+++ b/scene/grid.py
@@ -0,0 +1,63 @@
+import os
+import time
+import functools
+import numpy as np
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+parent_dir = os.path.dirname(os.path.abspath(__file__))
+
+
+def create_grid(type, **kwargs):
+    if type == 'DenseGrid':
+        return DenseGrid(**kwargs)
+    elif type == 'TensoRFGrid':
+        return TensoRFGrid(**kwargs)
+    else:
+        raise NotImplementedError
+
+
+''' Dense 3D grid
+'''
+class DenseGrid(nn.Module):
+    def __init__(self, channels, world_size, xyz_min, xyz_max, **kwargs):
+        super(DenseGrid, self).__init__()
+        self.channels = channels
+        self.world_size = world_size
+        self.register_buffer('xyz_min', torch.Tensor(xyz_min))
+        self.register_buffer('xyz_max', torch.Tensor(xyz_max))
+        self.grid = nn.Parameter(torch.zeros([1, channels, *world_size]))
+
+    def forward(self, xyz):
+        '''
+        xyz: global coordinates to query
+        '''
+        shape = xyz.shape[:-1]
+        xyz = xyz.reshape(1,1,1,-1,3)
+        ind_norm = ((xyz - self.xyz_min) / (self.xyz_max - self.xyz_min)).flip((-1,)) * 2 - 1
+        out = F.grid_sample(self.grid, ind_norm, mode='bilinear', align_corners=True)
+        out = out.reshape(self.channels,-1).T.reshape(*shape,self.channels)
+        if self.channels == 1:
+            out = out.squeeze(-1)
+        return out
+
+    def scale_volume_grid(self, new_world_size):
+        if self.channels == 0:
+            self.grid = nn.Parameter(torch.zeros([1, self.channels, *new_world_size]))
+        else:
+            self.grid = nn.Parameter(
+                F.interpolate(self.grid.data, size=tuple(new_world_size), mode='trilinear', align_corners=True))
+
+    def get_dense_grid(self):
+        return self.grid
+
+    @torch.no_grad()
+    def __isub__(self, val):
+        self.grid.data -= val
+        return self
+
+    def extra_repr(self):
+        return f'channels={self.channels}, world_size={self.world_size.tolist()}'
+
diff --git a/scene/neural_3D_dataset_NDC.py b/scene/neural_3D_dataset_NDC.py
index 63bbcad..ae90d5f 100644
--- a/scene/neural_3D_dataset_NDC.py
+++ b/scene/neural_3D_dataset_NDC.py
@@ -264,6 +264,7 @@ class Neural3D_NDC_Dataset(Dataset):
         self.near_fars = poses_arr[:, -2:]
         videos = glob.glob(os.path.join(self.root_dir, "cam*"))
         videos = sorted(videos)
+        breakpoint()
         assert len(videos) == poses_arr.shape[0]
 
         H, W, focal = poses[0, :, -1]
diff --git a/scripts/train_dynerf.sh b/scripts/train_dynerf.sh
index b8c07e2..48cc0b3 100644
--- a/scripts/train_dynerf.sh
+++ b/scripts/train_dynerf.sh
@@ -1,18 +1,27 @@
 exp_name=$1
-export CUDA_VISIBLE_DEVICES=0&&python train.py -s data/hypernerf/misc/split-cookie --port 6068 --expname "$exp_name/split-cookie" --configs arguments/$exp_name/default.py &
-export CUDA_VISIBLE_DEVICES=1&&python train.py -s data/hypernerf/virg/vrig-3dprinter --port 6066 --expname "$exp_name/3dprinter" --configs arguments/$exp_name/default.py &
-export CUDA_VISIBLE_DEVICES=2&&python train.py -s data/hypernerf/interp/chickchicken --port 6069 --expname "$exp_name/interp-chicken" --configs arguments/$exp_name/default.py  &
-export CUDA_VISIBLE_DEVICES=3&&python train.py -s data/hypernerf/interp/cut-lemon1 --port 6070 --expname "$exp_name/cut-lemon1" --configs arguments/$exp_name/cut-lemon1.py &
-# export CUDA_VISIBLE_DEVICES=3&&python train.py -s data/hypernerf/interp/hand1-dense-v2 --port 6071 --expname "$exp_name/hand1-dense-v2" --configs arguments/$exp_name/hand1-dense-v2.py 
+export CUDA_VISIBLE_DEVICES=0&&python train.py -s data/dynerf/cut_roasted_beef --port 6068 --expname "$exp_name/cut_roasted_beef" --configs arguments/$exp_name/default.py &
+export CUDA_VISIBLE_DEVICES=1&&python train.py -s data/dynerf/cook_spinach --port 6066 --expname "$exp_name/cook_spinach" --configs arguments/$exp_name/default.py &
+export CUDA_VISIBLE_DEVICES=2&&python train.py -s data/dynerf/sear_steak --port 6069 --expname "$exp_name/sear_steak" --configs arguments/$exp_name/default.py  &
 wait
-export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path output/$exp_name/cut_roasted_beef --configs arguments/$exp_name/default.py --skip_train --skip_test&
-export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path output/$exp_name/cook_spinach  --configs arguments/$exp_name/default.py --skip_train --skip_test &
-export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path output/$exp_name/sear_steak --configs arguments/$exp_name/default.py --skip_train --skip_test&
+export CUDA_VISIBLE_DEVICES=0&&python train.py -s data/dynerf/flame_salmon_1 --port 6070 --expname "$exp_name/flame_salmon_1" --configs arguments/$exp_name/default.py &
+export CUDA_VISIBLE_DEVICES=1&&python train.py -s data/dynerf/flame_steak --port 6071 --expname "$exp_name/flame_steak" --configs arguments/$exp_name/default.py &
+export CUDA_VISIBLE_DEVICES=2&&python train.py -s data/dynerf/coffee_martini --port 6071 --expname "$exp_name/coffee_martini" --configs arguments/$exp_name/default.py  &
+wait
+export CUDA_VISIBLE_DEVICES=0&&python render.py --model_path output/$exp_name/cut_roasted_beef --configs arguments/$exp_name/default.py --skip_train &
+export CUDA_VISIBLE_DEVICES=1&&python render.py --model_path output/$exp_name/cook_spinach  --configs arguments/$exp_name/default.py --skip_train  &
+export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path output/$exp_name/sear_steak --configs arguments/$exp_name/default.py --skip_train &
 # export CUDA_VISIBLE_DEVICES=3&&python render.py --model_path output/$exp_name/hand1-dense-v2 --configs arguments/$exp_name/hand1-dense-v2.py --skip_train
 wait
-export CUDA_VISIBLE_DEVICES=0&&python metrics.py --model_path "output/$exp_name/cut_roasted_beefe/"  &
+export CUDA_VISIBLE_DEVICES=0&&python render.py --model_path output/$exp_name/flame_salmon_1 --configs arguments/$exp_name/default.py --skip_train &
+export CUDA_VISIBLE_DEVICES=1&&python render.py --model_path output/$exp_name/flame_steak --configs arguments/$exp_name/default.py --skip_train &
+export CUDA_VISIBLE_DEVICES=2&&python render.py --model_path output/$exp_name/coffee_martini --configs arguments/$exp_name/default.py --skip_train &
+wait
+export CUDA_VISIBLE_DEVICES=0&&python metrics.py --model_path "output/$exp_name/cut_roasted_beef/"  &
 export CUDA_VISIBLE_DEVICES=1&&python metrics.py --model_path "output/$exp_name/cook_spinach/" &
 export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name/sear_steak/" &
 # export CUDA_VISIBLE_DEVICES=3&&python metrics.py --model_path "output/$exp_name/hand1-dense-v2/" 
 wait
+export CUDA_VISIBLE_DEVICES=0&&python metrics.py --model_path "output/$exp_name/flame_salmon_1/"  &
+export CUDA_VISIBLE_DEVICES=1&&python metrics.py --model_path "output/$exp_name/flame_steak/" &
+export CUDA_VISIBLE_DEVICES=2&&python metrics.py --model_path "output/$exp_name/coffee_martini/" &
 echo "Done"
\ No newline at end of file
diff --git a/train.py b/train.py
index 20f931e..9f6b0a1 100644
--- a/train.py
+++ b/train.py
@@ -89,7 +89,7 @@ def scene_reconstruction(dataset, opt, hyper, pipe, testing_iterations, saving_i
         # Pick a random Camera
         if not viewpoint_stack:
             viewpoint_stack = scene.getTrainCameras()
-            batch_size = 1
+            batch_size = opt.batch_size
             viewpoint_stack_loader = DataLoader(viewpoint_stack, batch_size=batch_size,shuffle=True,num_workers=32,collate_fn=list)
             loader = iter(viewpoint_stack_loader)
         if opt.dataloader:
@@ -97,7 +97,7 @@ def scene_reconstruction(dataset, opt, hyper, pipe, testing_iterations, saving_i
                 viewpoint_cams = next(loader)
             except StopIteration:
                 print("reset dataloader")
-                batch_size = 1
+                batch_size = opt.batch_size
                 loader = iter(viewpoint_stack_loader)
         else:
             idx = randint(0, len(viewpoint_stack)-1)