diff --git a/camera_estimation.py b/camera_estimation.py
index fbb04df..943f5ff 100644
--- a/camera_estimation.py
+++ b/camera_estimation.py
@@ -180,7 +180,7 @@ class TorchCameraEstimate(CameraEstimate):
         # camera_translation[0,2] = 5 * torch.ones(1)
 
         camera_rotation = torch.tensor(
-            [[1e-5, 1e-5, 1e-5]], requires_grad=True, dtype=self.dtype, device=self.device)
+            [[0,0,0]], requires_grad=False, dtype=self.dtype, device=self.device)
         camera_intrinsics = torch.zeros(
             4, 4, dtype=self.dtype, device=self.device)
         camera_intrinsics[0, 0] = 5
diff --git a/config.yaml b/config.yaml
index 23dab80..6b5bef3 100644
--- a/config.yaml
+++ b/config.yaml
@@ -21,17 +21,17 @@ camera:
 pose:
   # device: cuda
   lr: 0.05
-  optimizer: LBFGS # currently supported Adam, LBFGS
-  iterations: 300
+  optimizer: Adam # currently supported Adam, LBFGS
+  iterations: 100
   useCameraIntrinsics: false
   bodyMeanLoss:
     enabled: false
     weight: 0.001
   bodyPrior:
-    enabled: false
+    enabled: true
     weight: 2
   anglePrior:
-    enabled: true
+    enabled: false
     weight: 0.001
     # idxWeights:
     #   - 0.5
diff --git a/modules/camera.py b/modules/camera.py
index 49a1dea..eb92c96 100644
--- a/modules/camera.py
+++ b/modules/camera.py
@@ -48,7 +48,7 @@ class SimpleCamera(nn.Module):
             dtype,
             device,
             transform_mat=cam_trans,
-            #   camera_intrinsics=camera_int, camera_trans_rot=camera_params
+              camera_intrinsics=cam_int, camera_trans_rot=cam_params
         ), cam_trans, cam_int, cam_params
 
     def forward(self, points):
@@ -59,7 +59,7 @@ class SimpleCamera(nn.Module):
             return proj_points
         if self.hasCameraTransform:
             proj_points = self.cam_int[:3, :3] @ self.cam_trans_rot[:3,
-                                                                    :] @ points.reshape(-1, 4, 1)
+                                                                    :] @ self.trans @ points.reshape(-1, 4, 1)
             result = proj_points.squeeze(2)
             denomiator = torch.zeros(points.shape[1], 3)
             for i in range(points.shape[1]):