diff --git a/tensorflow/lite/delegates/xnnpack/xnnpack_delegate.cc b/tensorflow/lite/delegates/xnnpack/xnnpack_delegate.cc
index 925ef82ddcb..7c061b3a734 100644
--- a/tensorflow/lite/delegates/xnnpack/xnnpack_delegate.cc
+++ b/tensorflow/lite/delegates/xnnpack/xnnpack_delegate.cc
@@ -17,6 +17,7 @@ limitations under the License.
 
 #include <algorithm>
 #include <cstdint>
+#include <cstring>
 #include <limits>
 #include <memory>
 #include <string>
@@ -397,6 +398,27 @@ class Subgraph {
     return kTfLiteOk;
   }
 
+  static TfLiteStatus CheckTransposedConvolutionParams(
+      TfLiteContext* context, const TfLiteTransposeConvParams* params,
+      int node_index) {
+    if (params->stride_width <= 0) {
+      if (context != nullptr) {
+        TF_LITE_KERNEL_LOG(context, "invalid stride width %d in node #%d",
+                           params->stride_width, node_index);
+      }
+      return kTfLiteError;
+    }
+    if (params->stride_height <= 0) {
+      if (context != nullptr) {
+        TF_LITE_KERNEL_LOG(context, "invalid stride height %d in node #%d",
+                           params->stride_height, node_index);
+      }
+      return kTfLiteError;
+    }
+
+    return kTfLiteOk;
+  }
+
   static TfLiteStatus CheckFullyConnectedParams(
       TfLiteContext* context, const TfLiteFullyConnectedParams* params,
       int node_index) {
@@ -672,6 +694,18 @@ class Subgraph {
                                 context->tensors, softmax_params,
                                 xnnpack_tensors);
       }
+      case kTfLiteBuiltinCustom: {
+        if (strcmp(registration->custom_name, "Convolution2DTransposeBias") ==
+            0) {
+          const TfLiteTransposeConvParams* deconv_params =
+              static_cast<const TfLiteTransposeConvParams*>(
+                  node->custom_initial_data);
+          return VisitMediaPipeDeconvolutionNode(
+              subgraph, context, node_index, node, context->tensors,
+              deconv_params, xnnpack_tensors);
+        }
+        return kTfLiteError;
+      }
       default:
         return kTfLiteError;
     }
@@ -1236,6 +1270,93 @@ class Subgraph {
     return kTfLiteOk;
   }
 
+  static TfLiteStatus VisitMediaPipeDeconvolutionNode(
+      xnn_subgraph_t subgraph, TfLiteContext* logging_context, int node_index,
+      TfLiteNode* node, const TfLiteTensor* tensors,
+      const TfLiteTransposeConvParams* deconv_params,
+      const std::vector<uint32_t>& xnnpack_tensors) {
+    TF_LITE_ENSURE_STATUS(
+        CheckNumInputsAndOutputs(logging_context, node, 3, 1, node_index));
+
+    const TfLiteTensor& input_tensor = tensors[node->inputs->data[0]];
+    TF_LITE_ENSURE_STATUS(CheckTensorFloatType(
+        logging_context, input_tensor, node->inputs->data[0], node_index));
+    TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, input_tensor, 4,
+                                           node->inputs->data[0]));
+    TF_LITE_ENSURE_STATUS(CheckTensorNonDynamicAllocation(
+        logging_context, input_tensor, node->inputs->data[0], node_index));
+
+    const TfLiteTensor& filter_tensor = tensors[node->inputs->data[1]];
+    TF_LITE_ENSURE_STATUS(CheckTensorFloatType(
+        logging_context, filter_tensor, node->inputs->data[1], node_index));
+    TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, filter_tensor, 4,
+                                           node->inputs->data[1]));
+    TF_LITE_ENSURE_STATUS(CheckTensorStaticAllocation(
+        logging_context, filter_tensor, node->inputs->data[1], node_index));
+
+    const TfLiteTensor& bias_tensor = tensors[node->inputs->data[2]];
+    TF_LITE_ENSURE_STATUS(CheckTensorFloatType(
+        logging_context, filter_tensor, node->inputs->data[2], node_index));
+    TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, bias_tensor, 1,
+                                           node->inputs->data[2]));
+    TF_LITE_ENSURE_STATUS(CheckTensorStaticAllocation(
+        logging_context, bias_tensor, node->inputs->data[2], node_index));
+
+    const TfLiteTensor& output_tensor = tensors[node->outputs->data[0]];
+    TF_LITE_ENSURE_STATUS(CheckTensorFloatType(
+        logging_context, output_tensor, node->outputs->data[0], node_index));
+    TF_LITE_ENSURE_STATUS(CheckTensorShape(logging_context, output_tensor, 4,
+                                           node->outputs->data[0]));
+    TF_LITE_ENSURE_STATUS(CheckTensorNonDynamicAllocation(
+        logging_context, output_tensor, node->outputs->data[0], node_index));
+
+    const int output_channels = filter_tensor.dims->data[0];
+    const int kernel_height = filter_tensor.dims->data[1];
+    const int kernel_width = filter_tensor.dims->data[2];
+    const int input_channels = filter_tensor.dims->data[3];
+
+    TF_LITE_ENSURE_STATUS(CheckTransposedConvolutionParams(
+        logging_context, deconv_params, node_index));
+
+    uint32_t flags = 0;
+    TF_LITE_ENSURE_STATUS(CalculatePadding(
+        logging_context, deconv_params->padding, &flags, node_index));
+
+    if (subgraph != nullptr) {
+      const xnn_status status = xnn_define_deconvolution_2d(
+          subgraph,
+          /*padding_top=*/0,
+          /*padding_right=*/0,
+          /*padding_bottom=*/0,
+          /*padding_left=*/0,
+          /*adjustment_height=*/0,
+          /*adjustment_width=*/0, static_cast<uint32_t>(kernel_height),
+          static_cast<uint32_t>(kernel_width),
+          static_cast<uint32_t>(deconv_params->stride_height),
+          static_cast<uint32_t>(deconv_params->stride_width),
+          /*dilation_height=*/1,
+          /*dilation_width=*/1,
+          /*groups=*/1,
+          /*group_input_channels=*/input_channels,
+          /*group_output_channels=*/output_channels,
+          /*output_min=*/-std::numeric_limits<float>::infinity(),
+          /*output_max=*/+std::numeric_limits<float>::infinity(),
+          /*input_id=*/xnnpack_tensors[node->inputs->data[0]],
+          /*filter_id=*/xnnpack_tensors[node->inputs->data[1]],
+          /*bias_id=*/xnnpack_tensors[node->inputs->data[2]],
+          /*output_id=*/xnnpack_tensors[node->outputs->data[0]], flags);
+      if (status != xnn_status_success) {
+        TF_LITE_KERNEL_LOG(
+            logging_context,
+            "failed to delegate Convolution2DTransposeBias node #%d",
+            node_index);
+        return kTfLiteError;
+      }
+    }
+
+    return kTfLiteOk;
+  }
+
   static TfLiteStatus VisitMulNode(
       xnn_subgraph_t subgraph, TfLiteContext* logging_context, int node_index,
       TfLiteNode* node, const TfLiteTensor* tensors,
diff --git a/tensorflow/workspace.bzl b/tensorflow/workspace.bzl
index b613bc569ff..9d7fc8be5e8 100755
--- a/tensorflow/workspace.bzl
+++ b/tensorflow/workspace.bzl
@@ -156,11 +156,11 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""):
 
     tf_http_archive(
         name = "XNNPACK",
-        sha256 = "f6eb0f1759eca187d922a72a3a12dfe1593bd09783aa4b67bee70630985eb832",
-        strip_prefix = "XNNPACK-38c07ec51af0cbacb255922fb6219df80c06df59",
+        sha256 = "41a0a396a5a9cb2171c1c7f6d7689316beaa6f638663161fc7f86450eba33070",
+        strip_prefix = "XNNPACK-5871703602c459b98c12be301c01255ae68a45e2",
         urls = [
-            "https://storage.googleapis.com/mirror.tensorflow.org/github.com/google/XNNPACK/archive/38c07ec51af0cbacb255922fb6219df80c06df59.zip",
-            "https://github.com/google/XNNPACK/archive/38c07ec51af0cbacb255922fb6219df80c06df59.zip",
+            "https://storage.googleapis.com/mirror.tensorflow.org/github.com/google/XNNPACK/archive/5871703602c459b98c12be301c01255ae68a45e2.zip",
+            "https://github.com/google/XNNPACK/archive/5871703602c459b98c12be301c01255ae68a45e2.zip",
         ],
     )