diff --git a/src/backends/reference/workloads/Resize.cpp b/src/backends/reference/workloads/Resize.cpp
new file mode 100644
index 0000000..0e0bdd7
--- /dev/null
+++ b/src/backends/reference/workloads/Resize.cpp
@@ -0,0 +1,130 @@
+﻿//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "Resize.hpp"
+
+#include "TensorBufferArrayView.hpp"
+
+#include <boost/numeric/conversion/cast.hpp>
+
+#include <cmath>
+#include <algorithm>
+
+using namespace armnnUtils;
+
+namespace armnn
+{
+
+namespace
+{
+
+inline float Lerp(float a, float b, float w)
+{
+    return w * b + (1.f - w) * a;
+}
+
+}// anonymous namespace
+
+void Resize(Decoder<float>&   in,
+            const TensorInfo& inputInfo,
+            Encoder<float>&   out,
+            const TensorInfo& outputInfo,
+            DataLayoutIndexed dataLayout,
+            armnn::ResizeMethod resizeMethod)
+{
+    // We follow the definition of TensorFlow and AndroidNN: the top-left corner of a texel in the output
+    // image is projected into the input image to figure out the interpolants and weights. Note that this
+    // will yield different results than if projecting the centre of output texels.
+
+    const unsigned int batchSize = inputInfo.GetShape()[0];
+    const unsigned int channelCount = inputInfo.GetShape()[dataLayout.GetChannelsIndex()];
+
+    const unsigned int inputHeight = inputInfo.GetShape()[dataLayout.GetHeightIndex()];
+    const unsigned int inputWidth = inputInfo.GetShape()[dataLayout.GetWidthIndex()];
+    const unsigned int outputHeight = outputInfo.GetShape()[dataLayout.GetHeightIndex()];
+    const unsigned int outputWidth = outputInfo.GetShape()[dataLayout.GetWidthIndex()];
+
+    // How much to scale pixel coordinates in the output image, to get the corresponding pixel coordinates
+    // in the input image.
+    const float scaleY = boost::numeric_cast<float>(inputHeight) / boost::numeric_cast<float>(outputHeight);
+    const float scaleX = boost::numeric_cast<float>(inputWidth) / boost::numeric_cast<float>(outputWidth);
+
+    TensorShape inputShape =  inputInfo.GetShape();
+    TensorShape outputShape =  outputInfo.GetShape();
+
+    for (unsigned int n = 0; n < batchSize; ++n)
+    {
+        for (unsigned int c = 0; c < channelCount; ++c)
+        {
+            for (unsigned int y = 0; y < outputHeight; ++y)
+            {
+                // Corresponding real-valued height coordinate in input image.
+                const float iy = boost::numeric_cast<float>(y) * scaleY;
+
+                // Discrete height coordinate of top-left texel (in the 2x2 texel area used for interpolation).
+                const float fiy = floorf(iy);
+                const unsigned int y0 = boost::numeric_cast<unsigned int>(fiy);
+
+                // Interpolation weight (range [0,1]).
+                const float yw = iy - fiy;
+
+                for (unsigned int x = 0; x < outputWidth; ++x)
+                {
+                    // Real-valued and discrete width coordinates in input image.
+                    const float ix = boost::numeric_cast<float>(x) * scaleX;
+                    const float fix = floorf(ix);
+                    const unsigned int x0 = boost::numeric_cast<unsigned int>(fix);
+
+                    // Interpolation weight (range [0,1]).
+                    const float xw = ix - fix;
+
+                    // Discrete width/height coordinates of texels below and to the right of (x0, y0).
+                    const unsigned int x1 = std::min(x0 + 1, inputWidth - 1u);
+                    const unsigned int y1 = std::min(y0 + 1, inputHeight - 1u);
+
+                    float interpolatedValue;
+                    switch (resizeMethod)
+                    {
+                        case armnn::ResizeMethod::Bilinear:
+                        {
+                            in[dataLayout.GetIndex(inputShape, n, c, y0, x0)];
+                            float input1 = in.Get();
+                            in[dataLayout.GetIndex(inputShape, n, c, y0, x1)];
+                            float input2 = in.Get();
+                            in[dataLayout.GetIndex(inputShape, n, c, y1, x0)];
+                            float input3 = in.Get();
+                            in[dataLayout.GetIndex(inputShape, n, c, y1, x1)];
+                            float input4 = in.Get();
+
+                            const float ly0 = Lerp(input1, input2, xw); // lerp along row y0.
+                            const float ly1 = Lerp(input3, input4, xw); // lerp along row y1.
+                            interpolatedValue = Lerp(ly0, ly1, yw);
+                            break;
+                        }
+                        case armnn::ResizeMethod::NearestNeighbor:
+                        default:
+                        {
+                            auto distance0 = std::sqrt(pow(fix - boost::numeric_cast<float>(x0), 2) + 
+                                                       pow(fiy - boost::numeric_cast<float>(y0), 2));
+                            auto distance1 = std::sqrt(pow(fix - boost::numeric_cast<float>(x1), 2) +
+                                                       pow(fiy - boost::numeric_cast<float>(y1), 2));
+
+                            unsigned int xNearest = distance0 <= distance1? x0 : x1;
+                            unsigned int yNearest = distance0 <= distance1? y0 : y1;
+
+                            in[dataLayout.GetIndex(inputShape, n, c, yNearest, xNearest)];
+                            interpolatedValue = in.Get();
+                            break;
+                        }
+                    }
+                    out[dataLayout.GetIndex(outputShape, n, c, y, x)];
+                    out.Set(interpolatedValue);
+                }
+            }
+        }
+    }
+}
+
+} //namespace armnn