diff --git a/tensorflow/core/kernels/image/crop_and_resize_op.cc b/tensorflow/core/kernels/image/crop_and_resize_op.cc
index 41e30e543c1085..571e54a5a15700 100644
--- a/tensorflow/core/kernels/image/crop_and_resize_op.cc
+++ b/tensorflow/core/kernels/image/crop_and_resize_op.cc
@@ -170,14 +170,15 @@ class CropAndResizeOp : public AsyncOpKernel {
         context, crop_height > 0 && crop_width > 0,
         errors::InvalidArgument("crop dimensions must be positive"), done);
 
+    TensorShape shape;
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(num_boxes), done);
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(crop_height), done);
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(crop_width), done);
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(depth), done);
     // Allocate output tensor.
     Tensor* output = nullptr;
-    OP_REQUIRES_OK_ASYNC(
-        context,
-        context->allocate_output(
-            0, TensorShape({num_boxes, crop_height, crop_width, depth}),
-            &output),
-        done);
+    OP_REQUIRES_OK_ASYNC(context, context->allocate_output(0, shape, &output),
+                         done);
 
     auto compute_callback = [this, context, output]() {
       const Tensor& image = context->input(0);
@@ -417,14 +418,15 @@ class CropAndResizeGradImageOp : public AsyncOpKernel {
           done);
     }
 
+    TensorShape shape;
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(batch_size), done);
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(image_height), done);
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(image_width), done);
+    OP_REQUIRES_OK_ASYNC(context, shape.AddDimWithStatus(depth), done);
     // Allocate output tensor.
     Tensor* output = nullptr;
-    OP_REQUIRES_OK_ASYNC(
-        context,
-        context->allocate_output(
-            0, TensorShape({batch_size, image_height, image_width, depth}),
-            &output),
-        done);
+    OP_REQUIRES_OK_ASYNC(context, context->allocate_output(0, shape, &output),
+                         done);
 
     auto compute_callback = [this, context, output]() {
       const Tensor& grads = context->input(0);
diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py
index bfe4671328f460..86ac731a3080fe 100644
--- a/tensorflow/python/ops/image_ops_test.py
+++ b/tensorflow/python/ops/image_ops_test.py
@@ -6051,6 +6051,16 @@ def testImageCropAndResize(self):
             crop_size=[1, 1])
         self.evaluate(op)
 
+  def testImageCropAndResizeWithInvalidInput(self):
+    with self.session():
+      with self.assertRaises((errors.InternalError, ValueError)):
+        op = image_ops_impl.crop_and_resize_v2(
+            image=np.ones((1, 1, 1, 1)),
+            boxes=np.ones((11, 4)),
+            box_indices=np.ones((11)),
+            crop_size=[2065374891, 1145309325])
+        self.evaluate(op)
+
   @parameterized.named_parameters(
       ("_jpeg", "JPEG", "jpeg_merge_test1.jpg"),
       ("_png", "PNG", "lena_rgba.png"),