diff --git a/docs/source/transforms.rst b/docs/source/transforms.rst
index 1dec6bedf15..8e3c60085de 100644
--- a/docs/source/transforms.rst
+++ b/docs/source/transforms.rst
@@ -191,6 +191,7 @@ Miscellaneous
     Lambda
     v2.Lambda
     v2.SanitizeBoundingBox
+    v2.ClampBoundingBox
 
 .. _conversion_transforms:
 
@@ -212,6 +213,7 @@ Conversion
     v2.ConvertImageDtype
     v2.ConvertDtype
     v2.ToDtype
+    v2.ConvertBoundingBoxFormat
 
 Auto-Augmentation
 -----------------
diff --git a/torchvision/transforms/v2/_meta.py b/torchvision/transforms/v2/_meta.py
index 7d0f0ec39f9..94ec851d045 100644
--- a/torchvision/transforms/v2/_meta.py
+++ b/torchvision/transforms/v2/_meta.py
@@ -9,6 +9,15 @@
 
 
 class ConvertBoundingBoxFormat(Transform):
+    """[BETA] Convert bounding box coordinates to the given ``format``, e.g. from "CXCYWH" to "XYXY".
+
+    .. betastatus:: ConvertBoundingBoxFormat transform
+
+    Args:
+        format (str or datapoints.BoundingBoxFormat): output bounding box format.
+            Possible values are defined by :class:`~torchvision.datapoints.BoundingBoxFormat` and
+            string values match the enums, e.g. "XYXY" or "XYWH" etc.
+    """
     _transformed_types = (datapoints.BoundingBox,)
 
     def __init__(self, format: Union[str, datapoints.BoundingBoxFormat]) -> None:
@@ -22,7 +31,7 @@ def _transform(self, inpt: datapoints.BoundingBox, params: Dict[str, Any]) -> da
 
 
 class ConvertDtype(Transform):
-    """[BETA] Convert a tensor image/box/mask to the given ``dtype`` and scale the values accordingly
+    """[BETA] Convert input image or video to the given ``dtype`` and scale the values accordingly.
 
     .. betastatus:: ConvertDtype transform
 
@@ -63,6 +72,13 @@ def _transform(
 
 
 class ClampBoundingBox(Transform):
+    """[BETA] Clamp bounding boxes to their corresponding image dimensions.
+
+    The clamping is done according to the bounding boxes' ``spatial_size`` meta-data.
+
+    .. betastatus:: ClampBoundingBox transform
+
+    """
     _transformed_types = (datapoints.BoundingBox,)
 
     def _transform(self, inpt: datapoints.BoundingBox, params: Dict[str, Any]) -> datapoints.BoundingBox: