diff --git a/torchvision/io/_video_opt.py b/torchvision/io/_video_opt.py
index 4c39529b950..e28c565bce7 100644
--- a/torchvision/io/_video_opt.py
+++ b/torchvision/io/_video_opt.py
@@ -26,7 +26,6 @@
 
 # simple class for torch scripting
 # the complex Fraction class from fractions module is not scriptable
-@torch.jit.script
 class Timebase(object):
     __annotations__ = {"numerator": int, "denominator": int}
     __slots__ = ["numerator", "denominator"]
@@ -41,7 +40,6 @@ def __init__(
         self.denominator = denominator
 
 
-@torch.jit.script
 class VideoMetaData(object):
     __annotations__ = {
         "has_video": bool,
diff --git a/torchvision/models/detection/_utils.py b/torchvision/models/detection/_utils.py
index 10a13f37e6d..fedd5dc4a37 100644
--- a/torchvision/models/detection/_utils.py
+++ b/torchvision/models/detection/_utils.py
@@ -15,7 +15,6 @@ def zeros_like(tensor, dtype):
                             device=tensor.device, pin_memory=tensor.is_pinned())
 
 
-@torch.jit.script
 class BalancedPositiveNegativeSampler(object):
     """
     This class samples batches, ensuring that they contain a fixed proportion of positives
@@ -133,7 +132,6 @@ def encode_boxes(reference_boxes, proposals, weights):
     return targets
 
 
-@torch.jit.script
 class BoxCoder(object):
     """
     This class encodes and decodes a set of bounding boxes into
@@ -228,7 +226,6 @@ def decode_single(self, rel_codes, boxes):
         return pred_boxes
 
 
-@torch.jit.script
 class Matcher(object):
     """
     This class assigns to each predicted "element" (e.g., a box) a ground-truth
diff --git a/torchvision/models/detection/image_list.py b/torchvision/models/detection/image_list.py
index e805e70163b..ca0f5b20c31 100644
--- a/torchvision/models/detection/image_list.py
+++ b/torchvision/models/detection/image_list.py
@@ -6,7 +6,6 @@
 from torch import Tensor
 
 
-@torch.jit.script
 class ImageList(object):
     """
     Structure that holds a list of images (of possibly
diff --git a/torchvision/ops/poolers.py b/torchvision/ops/poolers.py
index 0e43a896cac..d2af3b75235 100644
--- a/torchvision/ops/poolers.py
+++ b/torchvision/ops/poolers.py
@@ -39,7 +39,6 @@ def initLevelMapper(k_min, k_max, canonical_scale=224, canonical_level=4, eps=1e
     return LevelMapper(k_min, k_max, canonical_scale, canonical_level, eps)
 
 
-@torch.jit.script
 class LevelMapper(object):
     """Determine which FPN level each RoI in a set of RoIs should map to based
     on the heuristic in the FPN paper.