diff --git a/supervision/__init__.py b/supervision/__init__.py
index e3fcd26d..fa6e6044 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -13,6 +13,7 @@ from supervision.annotators.core import (
     BoxMaskAnnotator,
     CircleAnnotator,
     EllipseAnnotator,
+    HaloAnnotator,
     LabelAnnotator,
     MaskAnnotator,
     TraceAnnotator,
diff --git a/supervision/annotators/core.py b/supervision/annotators/core.py
index 2ee7c972..494c94ad 100644
--- a/supervision/annotators/core.py
+++ b/supervision/annotators/core.py
@@ -229,6 +229,88 @@ class BoxMaskAnnotator(BaseAnnotator):
         return scene
 
 
+class HaloAnnotator(BaseAnnotator):
+    """
+    A class for drawing Halos on an image using provided detections.
+    """
+
+    def __init__(
+        self,
+        color: Union[Color, ColorPalette] = ColorPalette.default(),
+        opacity: float = 0.8,
+        color_map: str = "class",
+        kernel_size: int = 40,
+    ):
+        """
+        Args:
+            color (Union[Color, ColorPalette]): The color or color palette to use for
+                annotating detections.
+            opacity (float): Opacity of the overlay mask. Must be between `0` and `1`.
+            color_map (str): Strategy for mapping colors to annotations.
+                Options are `index`, `class`, or `track`.
+            kernel_size (int): The size of the average pooling kernel used for creating the halo.
+        """
+        self.color: Union[Color, ColorPalette] = color
+        self.opacity = opacity
+        self.color_map: ColorMap = ColorMap(color_map)
+        self.kernel_size: int = kernel_size
+
+    def annotate(self, scene: np.ndarray, detections: Detections) -> np.ndarray:
+        """
+        Annotates the given scene with halos based on the provided detections.
+
+        Args:
+            scene (np.ndarray): The image where masks will be drawn.
+            detections (Detections): Object detections to annotate.
+
+        Returns:
+            np.ndarray: The annotated image.
+
+        Example:
+            ```python
+            >>> import supervision as sv
+
+            >>> image = ...
+            >>> detections = sv.Detections(...)
+
+            >>> halo_annotator = sv.HaloAnnotator()
+            >>> annotated_frame = halo_annotator.annotate(
+            ...     scene=image.copy(),
+            ...     detections=detections
+            ... )
+            ```
+
+        ![halo-annotator-example](https://media.roboflow.com/
+        supervision-annotator-examples/halo-annotator-example.png)
+        """
+        if detections.mask is None:
+            return scene
+        colored_mask = np.zeros_like(scene, dtype=np.uint8)
+        fmask = np.array([False] * scene.shape[0] * scene.shape[1]).reshape(
+            scene.shape[0], scene.shape[1]
+        )
+
+        for detection_idx in np.flip(np.argsort(detections.area)):
+            idx = resolve_color_idx(
+                detections=detections,
+                detection_idx=detection_idx,
+                color_map=self.color_map,
+            )
+            color = resolve_color(color=self.color, idx=idx)
+            mask = detections.mask[detection_idx]
+            fmask = np.logical_or(fmask, mask)
+            color_bgr = color.as_bgr()
+            colored_mask[mask] = color_bgr
+
+        colored_mask = cv2.blur(colored_mask, (self.kernel_size, self.kernel_size))
+        colored_mask[fmask] = [0, 0, 0]
+        gray = cv2.cvtColor(colored_mask, cv2.COLOR_BGR2GRAY)
+        alpha = self.opacity * gray / gray.max()
+        alpha_mask = alpha[:, :, np.newaxis]
+        scene = np.uint8(scene * (1 - alpha_mask) + colored_mask * self.opacity)
+        return scene
+
+
 class EllipseAnnotator(BaseAnnotator):
     """
     A class for drawing ellipses on an image using provided detections.