diff --git a/detectron2/modeling/meta_arch/rcnn.py b/detectron2/modeling/meta_arch/rcnn.py
index b01c362baa..e5f66d1a3d 100644
--- a/detectron2/modeling/meta_arch/rcnn.py
+++ b/detectron2/modeling/meta_arch/rcnn.py
@@ -64,8 +64,8 @@ def __init__(
         if vis_period > 0:
             assert input_format is not None, "input_format is required for visualization!"
 
-        self.register_buffer("pixel_mean", torch.Tensor(pixel_mean).view(-1, 1, 1))
-        self.register_buffer("pixel_std", torch.Tensor(pixel_std).view(-1, 1, 1))
+        self.register_buffer("pixel_mean", torch.Tensor(pixel_mean).view(-1, 1, 1), False)
+        self.register_buffer("pixel_std", torch.Tensor(pixel_std).view(-1, 1, 1), False)
         assert (
             self.pixel_mean.shape == self.pixel_std.shape
         ), f"{self.pixel_mean} and {self.pixel_std} have different shapes!"
diff --git a/detectron2/modeling/meta_arch/retinanet.py b/detectron2/modeling/meta_arch/retinanet.py
index 74150ff56e..654f04cd5b 100644
--- a/detectron2/modeling/meta_arch/retinanet.py
+++ b/detectron2/modeling/meta_arch/retinanet.py
@@ -137,8 +137,8 @@ def __init__(
         self.vis_period = vis_period
         self.input_format = input_format
 
-        self.register_buffer("pixel_mean", torch.Tensor(pixel_mean).view(-1, 1, 1))
-        self.register_buffer("pixel_std", torch.Tensor(pixel_std).view(-1, 1, 1))
+        self.register_buffer("pixel_mean", torch.Tensor(pixel_mean).view(-1, 1, 1), False)
+        self.register_buffer("pixel_std", torch.Tensor(pixel_std).view(-1, 1, 1), False)
 
         """
         In Detectron1, loss is normalized by number of foreground samples in the batch.
diff --git a/detectron2/modeling/meta_arch/semantic_seg.py b/detectron2/modeling/meta_arch/semantic_seg.py
index 2957ae1c08..025344952e 100644
--- a/detectron2/modeling/meta_arch/semantic_seg.py
+++ b/detectron2/modeling/meta_arch/semantic_seg.py
@@ -35,8 +35,8 @@ def __init__(self, cfg):
         super().__init__()
         self.backbone = build_backbone(cfg)
         self.sem_seg_head = build_sem_seg_head(cfg, self.backbone.output_shape())
-        self.register_buffer("pixel_mean", torch.Tensor(cfg.MODEL.PIXEL_MEAN).view(-1, 1, 1))
-        self.register_buffer("pixel_std", torch.Tensor(cfg.MODEL.PIXEL_STD).view(-1, 1, 1))
+        self.register_buffer("pixel_mean", torch.Tensor(cfg.MODEL.PIXEL_MEAN).view(-1, 1, 1), False)
+        self.register_buffer("pixel_std", torch.Tensor(cfg.MODEL.PIXEL_STD).view(-1, 1, 1), False)
 
     @property
     def device(self):
diff --git a/projects/Panoptic-DeepLab/panoptic_deeplab/panoptic_seg.py b/projects/Panoptic-DeepLab/panoptic_deeplab/panoptic_seg.py
index 29dcb27ad1..5062664e54 100644
--- a/projects/Panoptic-DeepLab/panoptic_deeplab/panoptic_seg.py
+++ b/projects/Panoptic-DeepLab/panoptic_deeplab/panoptic_seg.py
@@ -44,8 +44,8 @@ def __init__(self, cfg):
         self.backbone = build_backbone(cfg)
         self.sem_seg_head = build_sem_seg_head(cfg, self.backbone.output_shape())
         self.ins_embed_head = build_ins_embed_branch(cfg, self.backbone.output_shape())
-        self.register_buffer("pixel_mean", torch.Tensor(cfg.MODEL.PIXEL_MEAN).view(-1, 1, 1))
-        self.register_buffer("pixel_std", torch.Tensor(cfg.MODEL.PIXEL_STD).view(-1, 1, 1))
+        self.register_buffer("pixel_mean", torch.Tensor(cfg.MODEL.PIXEL_MEAN).view(-1, 1, 1), False)
+        self.register_buffer("pixel_std", torch.Tensor(cfg.MODEL.PIXEL_STD).view(-1, 1, 1), False)
         self.meta = MetadataCatalog.get(cfg.DATASETS.TRAIN[0])
         self.stuff_area = cfg.MODEL.PANOPTIC_DEEPLAB.STUFF_AREA
         self.threshold = cfg.MODEL.PANOPTIC_DEEPLAB.CENTER_THRESHOLD
diff --git a/projects/TensorMask/tensormask/arch.py b/projects/TensorMask/tensormask/arch.py
index 2746b7eb4e..6f5d815656 100644
--- a/projects/TensorMask/tensormask/arch.py
+++ b/projects/TensorMask/tensormask/arch.py
@@ -348,8 +348,8 @@ def __init__(self, cfg):
         )
         # box transform
         self.box2box_transform = Box2BoxTransform(weights=cfg.MODEL.TENSOR_MASK.BBOX_REG_WEIGHTS)
-        self.register_buffer("pixel_mean", torch.Tensor(cfg.MODEL.PIXEL_MEAN).view(-1, 1, 1))
-        self.register_buffer("pixel_std", torch.Tensor(cfg.MODEL.PIXEL_STD).view(-1, 1, 1))
+        self.register_buffer("pixel_mean", torch.Tensor(cfg.MODEL.PIXEL_MEAN).view(-1, 1, 1), False)
+        self.register_buffer("pixel_std", torch.Tensor(cfg.MODEL.PIXEL_STD).view(-1, 1, 1), False)
 
     @property
     def device(self):