diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index da81c0a..24fe7da 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -2168,35 +2168,22 @@
     auto inputTensorIndexes = AsUnsignedVector(GetInputTensorIds(m_Model, subgraphIndex, operatorIndex));
     RegisterInputSlots(subgraphIndex, operatorIndex, layer, {inputTensorIndexes[0]});
 
-    // Reshape to remove unpacked dimension
-    unsigned int reshapedNumDimensions = inputDimSize - 1;
-    std::vector<unsigned int> reshapedDimensions(reshapedNumDimensions);
-
-    unsigned int reshapeIndex = 0;
-    for (unsigned int i = 0; i < inputDimSize; ++i)
-    {
-        if (i == unpackAxis)
-        {
-            continue;
-        }
-        reshapedDimensions[reshapeIndex++] = unpackDimSizes[i];
-    }
-
     // Create reshape to remove the unpacked dimension for unpack operator of each output from Splitter.
     for (unsigned int k = 0; k < layer->GetNumOutputSlots(); ++k)
     {
-        armnn::TensorInfo reshapedTensorInfo = inputTensorInfo;
-        reshapedTensorInfo.SetShape(armnn::TensorShape{ reshapedNumDimensions, reshapedDimensions.data() });
-
+        armnn::TensorInfo outputTensorInfo  = ToTensorInfo(outputs[k]);
         std::string reshapeLayerName = boost::str(boost::format("Reshape_for:%1%") % layer->GetName());
         armnn::ReshapeDescriptor desc;
-        desc.m_TargetShape = reshapedTensorInfo.GetShape();
+        desc.m_TargetShape = outputTensorInfo.GetShape();
         armnn::IConnectableLayer* reshapeLayer = m_Network->AddReshapeLayer(desc, layerName.c_str());
 
-        layer->GetOutputSlot(k).SetTensorInfo(armnn::TensorInfo(splitOutShape, inputTensorInfo.GetDataType()));
+        layer->GetOutputSlot(k).SetTensorInfo(armnn::TensorInfo(splitOutShape,
+                                                                outputTensorInfo.GetDataType(),
+                                                                outputTensorInfo.GetQuantizationScale(),
+                                                                outputTensorInfo.GetQuantizationOffset()));
         layer->GetOutputSlot(k).Connect(reshapeLayer->GetInputSlot(0));
 
-        reshapeLayer->GetOutputSlot(0).SetTensorInfo(reshapedTensorInfo);
+        reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
 
         uint32_t reshapedOutputId = CHECKED_NON_NEGATIVE(operatorPtr->outputs[k]);
         armnn::IOutputSlot* slot = &(reshapeLayer->GetOutputSlot(0));
diff --git a/src/armnnTfLiteParser/test/Unpack.cpp b/src/armnnTfLiteParser/test/Unpack.cpp
index 6b3c57b..04fd50d 100644
--- a/src/armnnTfLiteParser/test/Unpack.cpp
+++ b/src/armnnTfLiteParser/test/Unpack.cpp
@@ -14,11 +14,14 @@
 
 struct UnpackFixture : public ParserFlatbuffersFixture
 {
-    explicit UnpackFixture(const std::string & inputShape,
+    explicit UnpackFixture(const std::string& inputShape,
                            const unsigned int numberOfOutputs,
-                           const std::string & outputShape,
-                           const std::string & axis,
-                           const std::string & num)
+                           const std::string& outputShape,
+                           const std::string& axis,
+                           const std::string& num,
+                           const std::string& dataType,
+                           const std::string& outputScale,
+                           const std::string& outputOffset)
     {
         // As input index is 0, output indexes start at 1
         std::string outputIndexes = "1";
@@ -34,7 +37,7 @@
                     "tensors": [
                         {
                             "shape": )" + inputShape + R"(,
-                            "type": "FLOAT32",
+                            "type": )" + dataType + R"(,
                             "buffer": 0,
                             "name": "inputTensor",
                             "quantization": {
@@ -51,14 +54,14 @@
             m_JsonString += R"(
                         {
                             "shape": )" + outputShape + R"( ,
-                                "type": "FLOAT32",
+                                "type": )" + dataType + R"(,
                                 "buffer": )" + std::to_string(i + 1) + R"(,
                                 "name": "outputTensor)" + std::to_string(i + 1) + R"(",
                                 "quantization": {
                                 "min": [ 0.0 ],
                                 "max": [ 255.0 ],
-                                "scale": [ 1.0 ],
-                                "zero_point": [ 0 ],
+                                "scale": [ )" + outputScale + R"( ],
+                                "zero_point": [ )" + outputOffset + R"( ],
                             }
                         },)";
         }
@@ -99,7 +102,12 @@
 
 struct DefaultUnpackAxisZeroFixture : UnpackFixture
 {
-    DefaultUnpackAxisZeroFixture() : UnpackFixture("[ 4, 1, 6 ]", 4, "[ 1, 6 ]", "0", "") {}
+    DefaultUnpackAxisZeroFixture() : UnpackFixture("[ 4, 1, 6 ]", 4, "[ 1, 6 ]", "0", "", "FLOAT32", "1.0", "0") {}
+};
+
+struct DefaultUnpackAxisZeroUint8Fixture : UnpackFixture
+{
+    DefaultUnpackAxisZeroUint8Fixture() : UnpackFixture("[ 4, 1, 6 ]", 4, "[ 1, 6 ]", "0", "", "UINT8", "0.1", "0") {}
 };
 
 BOOST_FIXTURE_TEST_CASE(UnpackAxisZeroNumIsDefaultNotSpecified, DefaultUnpackAxisZeroFixture)
@@ -111,14 +119,33 @@
                             13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f,
                             19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f } } },
         { {"outputTensor1", { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }},
-          {"outputTensor2", { 7.0f,  8.0f,  9.0f, 10.0f, 11.0f, 12.0f }},
+          {"outputTensor2", { 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f }},
           {"outputTensor3", { 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f }},
           {"outputTensor4", { 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f }} });
 }
 
+BOOST_FIXTURE_TEST_CASE(UnpackAxisZeroNumIsDefaultNotSpecifiedUint8, DefaultUnpackAxisZeroUint8Fixture)
+{
+    RunTest<2, armnn::DataType::QuantisedAsymm8>(
+        0,
+        { {"inputTensor", { 1, 2, 3, 4, 5, 6,
+                            7, 8, 9, 10, 11, 12,
+                            13, 14, 15, 16, 17, 18,
+                            19, 20, 21, 22, 23, 24 } } },
+        { {"outputTensor1", { 10, 20, 30, 40, 50, 60 }},
+          {"outputTensor2", { 70, 80, 90, 100, 110, 120 }},
+          {"outputTensor3", { 130, 140, 150, 160, 170, 180 }},
+          {"outputTensor4", { 190, 200, 210, 220, 230, 240 }} });
+}
+
 struct DefaultUnpackLastAxisFixture : UnpackFixture
 {
-    DefaultUnpackLastAxisFixture() : UnpackFixture("[ 4, 1, 6 ]", 6, "[ 4, 1 ]", "2", "6") {}
+    DefaultUnpackLastAxisFixture() : UnpackFixture("[ 4, 1, 6 ]", 6, "[ 4, 1 ]", "2", "6", "FLOAT32", "1.0", "0") {}
+};
+
+struct DefaultUnpackLastAxisUint8Fixture : UnpackFixture
+{
+    DefaultUnpackLastAxisUint8Fixture() : UnpackFixture("[ 4, 1, 6 ]", 6, "[ 4, 1 ]", "2", "6", "UINT8", "0.1", "0") {}
 };
 
 BOOST_FIXTURE_TEST_CASE(UnpackLastAxisNumSix, DefaultUnpackLastAxisFixture)
@@ -137,4 +164,19 @@
           {"outputTensor6", { 6.0f, 12.0f, 18.0f, 24.0f }} });
 }
 
+BOOST_FIXTURE_TEST_CASE(UnpackLastAxisNumSixUint8, DefaultUnpackLastAxisUint8Fixture) {
+    RunTest<2, armnn::DataType::QuantisedAsymm8>(
+        0,
+        {{"inputTensor", { 1, 2, 3, 4, 5, 6,
+                           7, 8, 9, 10, 11, 12,
+                           13, 14, 15, 16, 17, 18,
+                           19, 20, 21, 22, 23, 24 }}},
+        {{"outputTensor1", { 10, 70, 130, 190 }},
+         {"outputTensor2", { 20, 80, 140, 200 }},
+         {"outputTensor3", { 30, 90, 150, 210 }},
+         {"outputTensor4", { 40, 100, 160, 220 }},
+         {"outputTensor5", { 50, 110, 170, 230 }},
+         {"outputTensor6", { 60, 120, 180, 240 }}});
+}
+
 BOOST_AUTO_TEST_SUITE_END()