diff --git a/art/attacks/evasion/adversarial_patch/adversarial_patch_pytorch.py b/art/attacks/evasion/adversarial_patch/adversarial_patch_pytorch.py
index a43ce14687..1a88f4a875 100644
--- a/art/attacks/evasion/adversarial_patch/adversarial_patch_pytorch.py
+++ b/art/attacks/evasion/adversarial_patch/adversarial_patch_pytorch.py
@@ -41,7 +41,7 @@
 
     import torch
 
-    from art.utils import CLASSIFIER_NEURALNETWORK_TYPE
+    from art.utils import CLASSIFIER_NEURALNETWORK_TYPE, PYTORCH_OBJECT_DETECTOR_TYPE
 
 logger = logging.getLogger(__name__)
 
@@ -72,7 +72,7 @@ class AdversarialPatchPyTorch(EvasionAttack):
 
     def __init__(
         self,
-        estimator: "CLASSIFIER_NEURALNETWORK_TYPE",
+        estimator: "CLASSIFIER_NEURALNETWORK_TYPE | PYTORCH_OBJECT_DETECTOR_TYPE",
         rotation_max: float = 22.5,
         scale_min: float = 0.1,
         scale_max: float = 1.0,
@@ -91,7 +91,7 @@ def __init__(
         """
         Create an instance of the :class:`.AdversarialPatchPyTorch`.
 
-        :param estimator: A trained estimator.
+        :param estimator: A trained PyTorch estimator for classification or object detection.
         :param rotation_max: The maximum rotation applied to random patches. The value is expected to be in the
                range `[0, 180]`.
         :param scale_min: The minimum scaling applied to random patches. The value should be in the range `[0, 1]`,