diff --git a/examples/classify_image.py b/examples/classify_image.py
index a67acd0..29ac91d 100644
--- a/examples/classify_image.py
+++ b/examples/classify_image.py
@@ -76,7 +76,7 @@ def main():
     raise ValueError('Only support uint8 input type.')
 
   size = common.input_size(interpreter)
-  image = Image.open(args.input).convert('RGB').resize(size, Image.ANTIALIAS)
+  image = Image.open(args.input).convert('RGB').resize(size, Image.LANCZOS)
 
   # Image data must go through two transforms before running inference:
   # 1. normalization: f = (input - mean) / std
diff --git a/examples/detect_image.py b/examples/detect_image.py
index 9862f9e..82c5851 100644
--- a/examples/detect_image.py
+++ b/examples/detect_image.py
@@ -75,7 +75,7 @@ def main():
 
   image = Image.open(args.input)
   _, scale = common.set_resized_input(
-      interpreter, image.size, lambda size: image.resize(size, Image.ANTIALIAS))
+      interpreter, image.size, lambda size: image.resize(size, Image.LANCZOS))
 
   print('----INFERENCE TIME----')
   print('Note: The first inference is slow because it includes',
diff --git a/examples/model_pipelining_classify_image.py b/examples/model_pipelining_classify_image.py
index 03cb3b8..4c4be70 100644
--- a/examples/model_pipelining_classify_image.py
+++ b/examples/model_pipelining_classify_image.py
@@ -134,7 +134,7 @@ def main():
   size = common.input_size(runner.interpreters()[0])
   name = common.input_details(runner.interpreters()[0], 'name')
   image = np.array(
-      Image.open(args.input).convert('RGB').resize(size, Image.ANTIALIAS))
+      Image.open(args.input).convert('RGB').resize(size, Image.LANCZOS))
 
   def producer():
     for _ in range(args.count):
diff --git a/examples/movenet_pose_estimation.py b/examples/movenet_pose_estimation.py
index 7a9bea6..4b5f68b 100644
--- a/examples/movenet_pose_estimation.py
+++ b/examples/movenet_pose_estimation.py
@@ -58,7 +58,7 @@ def main():
   interpreter.allocate_tensors()
 
   img = Image.open(args.input)
-  resized_img = img.resize(common.input_size(interpreter), Image.ANTIALIAS)
+  resized_img = img.resize(common.input_size(interpreter), Image.LANCZOS)
   common.set_input(interpreter, resized_img)
 
   interpreter.invoke()
diff --git a/examples/semantic_segmentation.py b/examples/semantic_segmentation.py
index 8c99d28..747a0c0 100644
--- a/examples/semantic_segmentation.py
+++ b/examples/semantic_segmentation.py
@@ -109,9 +109,9 @@ def main():
   img = Image.open(args.input)
   if args.keep_aspect_ratio:
     resized_img, _ = common.set_resized_input(
-        interpreter, img.size, lambda size: img.resize(size, Image.ANTIALIAS))
+        interpreter, img.size, lambda size: img.resize(size, Image.LANCZOS))
   else:
-    resized_img = img.resize((width, height), Image.ANTIALIAS)
+    resized_img = img.resize((width, height), Image.LANCZOS)
     common.set_input(interpreter, resized_img)
 
   interpreter.invoke()
diff --git a/tests/detect_test.py b/tests/detect_test.py
index f5189c5..b840090 100644
--- a/tests/detect_test.py
+++ b/tests/detect_test.py
@@ -33,7 +33,7 @@ def get_objects(model_file, delegate, image_file, score_threshold=0.0):
   interpreter.allocate_tensors()
   image = Image.open(test_utils.test_data_path(image_file))
   _, scale = common.set_resized_input(
-      interpreter, image.size, lambda size: image.resize(size, Image.ANTIALIAS))
+      interpreter, image.size, lambda size: image.resize(size, Image.LANCZOS))
   interpreter.invoke()
   return detect.get_objects(
       interpreter, score_threshold=score_threshold, image_scale=scale)
diff --git a/tests/multiple_tpus_test.py b/tests/multiple_tpus_test.py
index 8fed115..5e93d3b 100644
--- a/tests/multiple_tpus_test.py
+++ b/tests/multiple_tpus_test.py
@@ -64,7 +64,7 @@ def detection_task(num_inferences):
           _, scale = common.set_resized_input(
               interpreter,
               img.size,
-              lambda size, image=img: image.resize(size, Image.ANTIALIAS))
+              lambda size, image=img: image.resize(size, Image.LANCZOS))
           interpreter.invoke()
           ret = detect.get_objects(
               interpreter, score_threshold=0.7, image_scale=scale)
diff --git a/tests/segment_test.py b/tests/segment_test.py
index 7aae040..634fe81 100644
--- a/tests/segment_test.py
+++ b/tests/segment_test.py
@@ -47,7 +47,7 @@ def segment_image(model_file, delegate, image_file, mask_file):
   interpreter.allocate_tensors()
 
   image = Image.open(test_utils.test_data_path(image_file)).resize(
-      common.input_size(interpreter), Image.ANTIALIAS)
+      common.input_size(interpreter), Image.LANCZOS)
   common.set_input(interpreter, image)
   interpreter.invoke()