diff --git a/src/cpu/kernels/CpuScaleKernel.cpp b/src/cpu/kernels/CpuScaleKernel.cpp
new file mode 100644
index 0000000..1108c7a
--- /dev/null
+++ b/src/cpu/kernels/CpuScaleKernel.cpp
@@ -0,0 +1,623 @@
+/*
+ * Copyright (c) 2016-2021 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "src/cpu/kernels/CpuScaleKernel.h"
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/Utility.h"
+#include "src/core/CPP/Validate.h"
+#include "src/core/NEON/wrapper/wrapper.h"
+#include "src/core/common/Registrars.h"
+#include "src/core/helpers/AutoConfiguration.h"
+#include "src/core/helpers/ScaleHelpers.h"
+#include "src/core/helpers/WindowHelpers.h"
+#include "src/core/utils/ScaleUtils.h"
+#include "src/cpu/kernels/scale/neon/list.h"
+#include "src/cpu/kernels/scale/sve/list.h"
+#include "support/Rounding.h"
+
+#include <arm_neon.h>
+#include <map>
+
+namespace arm_compute
+{
+namespace cpu
+{
+namespace kernels
+{
+namespace
+{
+struct ScaleSelectorData
+{
+    DataType       dt;
+    const CPUInfo &ci;
+};
+using ScaleSelectorPtr = std::add_pointer<bool(const ScaleSelectorData &data)>::type;
+using ScaleKernelPtr   = std::add_pointer<void(const ITensor *, ITensor *, const ITensor *, const ITensor *, const ITensor *,
+                                               InterpolationPolicy, BorderMode, PixelValue, float, bool, const Window &)>::type;
+struct ScaleKernel
+{
+    const char            *name;
+    const ScaleSelectorPtr is_selected;
+    ScaleKernelPtr         ukernel;
+};
+
+static const ScaleKernel available_kernels[] =
+{
+#if defined(ARM_COMPUTE_ENABLE_SVE)
+    {
+        "sve_fp16_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::F16 && data.ci.has_sve(); },
+        REGISTER_FP16_SVE(arm_compute::cpu::fp16_sve_scale)
+    },
+    {
+        "sve_fp32_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::F32 && data.ci.has_sve(); },
+        REGISTER_FP32_SVE(arm_compute::cpu::fp32_sve_scale)
+    },
+    {
+        "sve_qu8_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::QASYMM8 && data.ci.has_sve(); },
+        REGISTER_QASYMM8_SVE(arm_compute::cpu::qasymm8_sve_scale)
+    },
+    {
+        "sve_qs8_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::QASYMM8_SIGNED && data.ci.has_sve(); },
+        REGISTER_QASYMM8_SIGNED_SVE(arm_compute::cpu::qasymm8_signed_sve_scale)
+    },
+    {
+        "sve_u8_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::U8 && data.ci.has_sve(); },
+        REGISTER_INTEGER_SVE(arm_compute::cpu::u8_sve_scale)
+    },
+    {
+        "sve_s16_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::S16 && data.ci.has_sve(); },
+        REGISTER_INTEGER_SVE(arm_compute::cpu::s16_sve_scale)
+    },
+#endif /* defined(ARM_COMPUTE_ENABLE_SVE) */
+#if defined(ARM_COMPUTE_ENABLE_NEON)
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
+    {
+        "neon_fp16_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::F16 && data.ci.has_fp16(); },
+        REGISTER_FP16_NEON(arm_compute::cpu::common_neon_scale<float16_t>)
+    },
+#endif /* !defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) */
+    {
+        "neon_fp32_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::F32; },
+        REGISTER_FP32_NEON(arm_compute::cpu::common_neon_scale<float>)
+    },
+    {
+        "neon_qu8_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::QASYMM8; },
+        REGISTER_QASYMM8_NEON(arm_compute::cpu::qasymm8_neon_scale)
+    },
+    {
+        "neon_qs8_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::QASYMM8_SIGNED; },
+        REGISTER_QASYMM8_SIGNED_NEON(arm_compute::cpu::qasymm8_signed_neon_scale)
+    },
+    {
+        "neon_u8_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::U8; },
+        REGISTER_INTEGER_NEON(arm_compute::cpu::common_neon_scale<uint8_t>)
+    },
+    {
+        "neon_s16_scale",
+        [](const ScaleSelectorData & data) { return data.dt == DataType::S16; },
+        REGISTER_INTEGER_NEON(arm_compute::cpu::common_neon_scale<int16_t>)
+    },
+#endif /* defined(ARM_COMPUTE_ENABLE_NEON) */
+};
+
+/** Micro-kernel selector
+ *
+ * @param[in] data Selection data passed to help pick the appropriate micro-kernel
+ *
+ * @return A matching micro-kernel else nullptr
+ */
+const ScaleKernel *get_implementation(const ScaleSelectorData &data)
+{
+    for(const auto &uk : available_kernels)
+    {
+        if(uk.is_selected(data))
+        {
+            return &uk;
+        }
+    }
+    return nullptr;
+}
+
+Status validate_arguments(const ITensorInfo *src, const ITensorInfo *dx, const ITensorInfo *dy,
+                          const ITensorInfo *offsets, ITensorInfo *dst, const ScaleKernelInfo &info)
+{
+    const auto *uk = get_implementation(ScaleSelectorData{ src->data_type(), CPUInfo::get() });
+    ARM_COMPUTE_RETURN_ERROR_ON(uk == nullptr || uk->ukernel == nullptr);
+
+    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(dst);
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
+    ARM_COMPUTE_RETURN_ERROR_ON(dst == src);
+    ARM_COMPUTE_RETURN_ERROR_ON(info.sampling_policy != SamplingPolicy::CENTER && info.sampling_policy != SamplingPolicy::TOP_LEFT);
+    ARM_COMPUTE_UNUSED(info.constant_border_value);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.use_padding, "Padding is not supported");
+
+    const DataLayout data_layout   = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout;
+    const auto       width_index   = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+    const auto       height_index  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
+    const auto       output_width  = dst->dimension(width_index);
+    const auto       output_height = dst->dimension(height_index);
+    ARM_COMPUTE_RETURN_ERROR_ON(output_width == 0);
+    ARM_COMPUTE_RETURN_ERROR_ON(output_height == 0);
+
+    if(info.interpolation_policy == InterpolationPolicy::NEAREST_NEIGHBOR)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(offsets, 1, DataType::S32);
+    }
+
+    if(info.interpolation_policy == InterpolationPolicy::BILINEAR)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(offsets, 1, DataType::S32);
+        if(dx != nullptr && dy != nullptr)
+        {
+            ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dx, 1, DataType::F32);
+            ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dy, 1, DataType::F32);
+        }
+    }
+
+    ARM_COMPUTE_RETURN_ERROR_ON(info.align_corners && !scale_utils::is_align_corners_allowed_sampling_policy(info.sampling_policy));
+
+    if(info.interpolation_policy == InterpolationPolicy::AREA)
+    {
+        ARM_COMPUTE_RETURN_ERROR_ON(data_layout != DataLayout::NCHW);
+        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::U8);
+    }
+
+    return Status{};
+}
+} // namespace
+
+void CpuScaleKernel::configure(const ITensorInfo *src, const ITensorInfo *dx, const ITensorInfo *dy, const ITensorInfo *offsets,
+                               ITensorInfo *dst, const ScaleKernelInfo &info)
+{
+    ARM_COMPUTE_UNUSED(dx, dy, offsets);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst);
+    // Perform validation step
+    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src,
+                                                  dx,
+                                                  dy,
+                                                  offsets,
+                                                  dst,
+                                                  info));
+
+    const auto *uk = get_implementation(ScaleSelectorData{ src->data_type(), CPUInfo::get() });
+    ARM_COMPUTE_ERROR_ON_NULLPTR(uk);
+
+    _run_method = uk->ukernel;
+    _name       = std::string("CpuScaleKernel").append("/").append(uk->name).append("_").append(string_from_interpolation_policy(info.interpolation_policy));
+
+    // Get data layout and width/height indices
+    _data_layout         = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout;
+    const int idx_width  = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
+    const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
+
+    _policy                = info.interpolation_policy;
+    _border_mode           = info.border_mode;
+    _constant_border_value = info.constant_border_value;
+    _align_corners         = info.align_corners;
+
+    if(info.sampling_policy == SamplingPolicy::CENTER)
+    {
+        _sampling_offset = 0.5f;
+    }
+
+    // Compute the ratio between source width/height and destination width/height
+    const auto wr = scale_utils::calculate_resize_ratio(src->dimension(idx_width), dst->dimension(idx_width), _align_corners);
+    const auto hr = scale_utils::calculate_resize_ratio(src->dimension(idx_height), dst->dimension(idx_height), _align_corners);
+
+    // Area interpolation behaves as Nearest Neighbour in case of up-sampling
+    _policy = (_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : _policy;
+
+    if(_border_mode == BorderMode::UNDEFINED)
+    {
+        _border_mode           = BorderMode::CONSTANT;
+        _constant_border_value = PixelValue();
+    }
+
+#ifdef ENABLE_NCHW_KERNELS
+    // Configure scale function to run
+    if(_data_layout == DataLayout::NCHW)
+    {
+        std::string function_to_call("scale_");
+        function_to_call += string_from_data_type(src->data_type()) + "_";
+        function_to_call += string_from_data_layout(_data_layout) + "_";
+        function_to_call += string_from_interpolation_policy(_policy);
+
+        static std::map<std::string, ScaleFunctionPtr> map_function =
+        {
+            { "scale_U8_NCHW_AREA_CONSTANT", &CpuScaleKernel::scale_area_nchw_u8 },
+
+            { "scale_U8_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<uint8_t> },
+            { "scale_U8_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<uint8_t> },
+
+            { "scale_QASYMM8_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_qasymm<uint8_t> },
+            { "scale_QASYMM8_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<uint8_t> },
+
+            { "scale_QASYMM8_SIGNED_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_qasymm<int8_t> },
+            { "scale_QASYMM8_SIGNED_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<int8_t> },
+
+            { "scale_S16_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<int16_t> },
+            { "scale_S16_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<int16_t> },
+
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+            { "scale_F16_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<float16_t> },
+            { "scale_F16_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<float16_t> },
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+
+            { "scale_F32_NCHW_BILINEAR", &CpuScaleKernel::scale_bilinear_nchw<float> },
+            { "scale_F32_NCHW_NEAREST_NEIGHBOUR", &CpuScaleKernel::scale_nearest_nchw<float> },
+        };
+        auto it = map_function.find(function_to_call);
+        if(it != map_function.end())
+        {
+            _func = it->second;
+        }
+    }
+#endif // ENABLE_NCHW_KERNELS
+
+    // Configure window
+    Window win = calculate_max_window(*dst, Steps());
+    ICpuKernel::configure(win);
+}
+
+#ifdef ENABLE_NCHW_KERNELS
+template <typename T>
+void CpuScaleKernel::scale_nearest_nchw(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window)
+{
+    ARM_COMPUTE_UNUSED(dx, dy);
+    const size_t in_stride_x = src->info()->dimension(0) + src->info()->padding().left + src->info()->padding().right;
+
+    // Compute the ratio between source height and destination height
+    const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(1), dst->info()->dimension(1), _align_corners);
+
+    // Don't increment in X and Y direction for the input tensor
+    // A pointer to the start of this plane is needed as base for the precomputed offsets
+    Window win_in(window);
+    win_in.set(Window::DimX, Window::Dimension(0, 0, 0));
+    win_in.set(Window::DimY, Window::Dimension(0, 0, 0));
+
+    // Set offsets window
+    Window win_off;
+    win_off.set(Window::DimX, window[Window::DimX]);
+    win_off.set(Window::DimY, window[Window::DimY]);
+    for(size_t d = Window::DimZ; d < offsets->info()->num_dimensions(); ++d)
+    {
+        win_off.set(d, Window::Dimension(0, 0, 0));
+    }
+
+    // Create iterators
+    Iterator src_i(src, win_in);
+    Iterator dst_i(dst, window);
+    Iterator offsets_i(offsets, win_off);
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        const auto offsets_ptr = reinterpret_cast<const int32_t *>(offsets_i.ptr());
+        const auto in_yi       = static_cast<int32_t>(_align_corners ? utils::rounding::round_half_away_from_zero((id.y() + _sampling_offset) * hr) : std::floor((
+                                                          id.y() + _sampling_offset)
+                                                      * hr));
+        const int32_t offset_row            = in_yi * in_stride_x;
+        *reinterpret_cast<T *>(dst_i.ptr()) = *(reinterpret_cast<const T *>(src_i.ptr()) + offsets_ptr[0] + offset_row);
+    },
+    src_i, offsets_i, dst_i);
+}
+
+template <typename T>
+void CpuScaleKernel::scale_bilinear_nchw(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window)
+{
+    // Compute the ratio between source height and destination height
+    const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(1), dst->info()->dimension(1), _align_corners);
+    Window     win_off;
+    win_off.set(Window::DimX, window.x());
+    win_off.set(Window::DimY, window.y());
+
+    // Don't increment in X and Y direction for the input tensor
+    // A pointer to the start of this plane is needed as base for the precomputed offsets
+    Window win_in(window);
+    win_in.set(Window::DimX, Window::Dimension(0, 0, 0));
+    win_in.set(Window::DimY, Window::Dimension(0, 0, 0));
+
+    for(size_t d = Window::DimZ; d < offsets->info()->num_dimensions(); ++d)
+    {
+        win_off.set(d, Window::Dimension(0, 0, 0));
+    }
+
+    Iterator src_i(src, win_in);
+    Iterator dst_i(dst, window);
+    Iterator offsets_i(offsets, win_off);
+    Iterator dx_i(dx, win_off);
+    Iterator dy_i(dy, win_off);
+
+    const int32_t in_dim_w    = src->info()->dimension(0);
+    const int32_t in_dim_h    = src->info()->dimension(1);
+    const int32_t in_stride_w = in_dim_w + src->info()->padding().left + src->info()->padding().right;
+
+    if(_border_mode == BorderMode::CONSTANT)
+    {
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+        using ConstType = typename std::conditional<std::is_same<T, float16_t>::value, half, T>::type;
+#else  /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+        using ConstType = T;
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+        const T const_border_value = static_cast<T>(_constant_border_value.get<ConstType>());
+        execute_window_loop(window, [&](const Coordinates & id)
+        {
+            const int32_t index_h       = std::floor((id.y() + _sampling_offset) * hr - _sampling_offset);
+            const auto    index_w       = *(reinterpret_cast<const int32_t *>(offsets_i.ptr()));
+            const auto    dx_val        = *(reinterpret_cast<const float *>(dx_i.ptr()));
+            const auto    dy_val        = *(reinterpret_cast<const float *>(dy_i.ptr()));
+            const auto    pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr());
+
+            const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ? (*(pixel_row_ptr + index_w + index_h * in_stride_w)) : const_border_value;
+            const auto a01 = (-1 <= index_w && index_w < in_dim_w - 1 && 0 <= index_h && index_h < in_dim_h) ? (*(pixel_row_ptr + index_w + 1 + index_h * in_stride_w)) : const_border_value;
+            const auto a10 = (0 <= index_w && index_w < in_dim_w && -1 <= index_h
+                              && index_h < in_dim_h - 1) ?
+                             (*(pixel_row_ptr + index_w + index_h * in_stride_w + in_stride_w)) :
+                             const_border_value;
+            const auto a11 = (-1 <= index_w && index_w < in_dim_w - 1 && -1 <= index_h
+                              && index_h < in_dim_h - 1) ?
+                             (*(pixel_row_ptr + index_w + 1 + index_h * in_stride_w + in_stride_w)) :
+                             const_border_value;
+
+            *reinterpret_cast<T *>(dst_i.ptr()) = static_cast<T>(scale_helpers::delta_bilinear(a00, a01, a10, a11, dx_val, dy_val));
+        },
+        src_i, offsets_i, dx_i, dy_i, dst_i);
+    }
+    else if(_border_mode == BorderMode::REPLICATE)
+    {
+        execute_window_loop(window, [&](const Coordinates & id)
+        {
+            const int  index_h       = std::floor((id.y() + _sampling_offset) * hr - _sampling_offset);
+            const auto index_w       = *(reinterpret_cast<const int32_t *>(offsets_i.ptr()));
+            const auto dx_val        = *(reinterpret_cast<const float *>(dx_i.ptr()));
+            const auto dy_val        = *(reinterpret_cast<const float *>(dy_i.ptr()));
+            const auto pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr());
+
+            auto clamped_x  = utility::clamp<int>(index_w, 0, in_dim_w - 1);
+            auto clamped_x1 = utility::clamp<int>(index_w + 1, 0, in_dim_w - 1);
+            auto clamped_y  = utility::clamp<int>(index_h, 0, in_dim_h - 1);
+            auto clamped_y1 = utility::clamp<int>(index_h + 1, 0, in_dim_h - 1);
+
+            const auto a00 = *(pixel_row_ptr + clamped_x + clamped_y * in_stride_w);
+            const auto a01 = *(pixel_row_ptr + clamped_x1 + clamped_y * in_stride_w);
+            const auto a10 = *(pixel_row_ptr + clamped_x + clamped_y1 * in_stride_w);
+            const auto a11 = *(pixel_row_ptr + clamped_x1 + clamped_y1 * in_stride_w);
+
+            *reinterpret_cast<T *>(dst_i.ptr()) = static_cast<T>(scale_helpers::delta_bilinear(a00, a01, a10, a11, dx_val, dy_val));
+        },
+        src_i, offsets_i, dx_i, dy_i, dst_i);
+    }
+    else
+    {
+        ARM_COMPUTE_ERROR("Not implemented");
+    }
+}
+
+void CpuScaleKernel::scale_area_nchw_u8(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window)
+{
+    ARM_COMPUTE_UNUSED(dx, dy, offsets);
+    using namespace scale_helpers;
+
+    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::U8);
+
+    // Don't increment in width/height/channels for the input tensor
+    // A pointer to the start of this plane is needed as base for the precomputed offsets
+    Window win_in(window);
+    win_in.set(Window::DimX, Window::Dimension(0, 0, 0));
+    win_in.set(Window::DimY, Window::Dimension(0, 0, 0));
+    win_in.set(Window::DimZ, Window::Dimension(0, 0, 0));
+
+    Iterator src_i(src, win_in);
+    Iterator dst_i(dst, window);
+
+    const auto   wr        = scale_utils::calculate_resize_ratio(src->info()->dimension(0), dst->info()->dimension(0), _align_corners);
+    const auto   hr        = scale_utils::calculate_resize_ratio(src->info()->dimension(1), dst->info()->dimension(1), _align_corners);
+    const auto   w         = src->info()->dimension(0);
+    const auto   h         = src->info()->dimension(1);
+    const size_t in_stride = src->info()->strides_in_bytes()[1];
+
+    execute_window_loop(window, [&](const Coordinates & id)
+    {
+        const auto in_ptr = reinterpret_cast<const uint8_t *>(src_i.ptr());
+
+        uint8x8_t tmp0 = vdup_n_u8(0);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x(), id.y()), tmp0, 0);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 1, id.y()), tmp0, 1);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 2, id.y()), tmp0, 2);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 3, id.y()), tmp0, 3);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 4, id.y()), tmp0, 4);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 5, id.y()), tmp0, 5);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 6, id.y()), tmp0, 6);
+        tmp0           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 7, id.y()), tmp0, 7);
+
+        uint8x8_t tmp1 = vdup_n_u8(0);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 8, id.y()), tmp1, 0);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 9, id.y()), tmp1, 1);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 10, id.y()), tmp1, 2);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 11, id.y()), tmp1, 3);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 12, id.y()), tmp1, 4);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 13, id.y()), tmp1, 5);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 14, id.y()), tmp1, 6);
+        tmp1           = vset_lane_u8(pixel_area_c1u8_clamp(in_ptr, in_stride, w, h, wr, hr, id.x() + 15, id.y()), tmp1, 7);
+
+        vst1q_u8(dst_i.ptr(), vcombine_u8(tmp0, tmp1));
+    },
+    src_i, dst_i);
+}
+
+template <typename T>
+void CpuScaleKernel::scale_bilinear_qasymm(const ITensor *src, ITensor *dst, const ITensor *dx, const ITensor *dy, const ITensor *offsets, const Window &window)
+{
+    // Get data layout and width/height indices
+    const int idx_width  = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH);
+    const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT);
+
+    // Compute the ratio between source height and destination height
+    const auto hr = scale_utils::calculate_resize_ratio(src->info()->dimension(idx_height), dst->info()->dimension(idx_height), _align_corners);
+    Window     win_off;
+    win_off.set(Window::DimX, Window::Dimension(0, 0, 0));
+    win_off.set(Window::DimY, Window::Dimension(0, 0, 0));
+
+    // Don't increment in X and Y direction for the input tensor
+    // A pointer to the start of this plane is needed as base for the precomputed offsets
+    Window win_in(window);
+    win_in.set(idx_width, Window::Dimension(0, 0, 0));
+    win_in.set(idx_height, Window::Dimension(0, 0, 0));
+
+    for(size_t d = Window::DimZ; d < offsets->info()->num_dimensions(); ++d)
+    {
+        win_off.set(d, Window::Dimension(0, 0, 0));
+    }
+
+    Iterator src_i(src, win_in);
+    Iterator dst_i(dst, window);
+
+    const int32_t in_dim_w = src->info()->dimension(idx_width);
+    const int32_t in_dim_h = src->info()->dimension(idx_height);
+    const int32_t stride_w = src->info()->strides_in_bytes()[idx_width];
+    const int32_t stride_h = src->info()->strides_in_bytes()[idx_height];
+
+    const UniformQuantizationInfo iq_info = src->info()->quantization_info().uniform();
+    const UniformQuantizationInfo oq_info = dst->info()->quantization_info().uniform();
+
+    if(_border_mode == BorderMode::CONSTANT)
+    {
+#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+        using ConstType = typename std::conditional<std::is_same<T, float16_t>::value, half, T>::type;
+#else  /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+        using ConstType = T;
+#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
+        const T const_border_value = static_cast<T>(_constant_border_value.get<ConstType>());
+        execute_window_loop(window, [&](const Coordinates & id)
+        {
+            const int32_t index_h       = std::floor((id[idx_height] + _sampling_offset) * hr - _sampling_offset);
+            const int32_t index_w       = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
+            const auto    dx_val        = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
+            const auto    dy_val        = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
+            const auto    pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr());
+
+            const auto a00 = (0 <= index_w && index_w < in_dim_w && 0 <= index_h && index_h < in_dim_h) ?
+                             (*(pixel_row_ptr + index_w * stride_w + index_h * stride_h)) :
+                             const_border_value;
+            const auto a01 = (-1 <= index_w && index_w < in_dim_w - 1 && 0 <= index_h && index_h < in_dim_h) ?
+                             (*(pixel_row_ptr + (index_w + 1) * stride_w + index_h * stride_h)) :
+                             const_border_value;
+            const auto a10 = (0 <= index_w && index_w < in_dim_w && -1 <= index_h && index_h < in_dim_h - 1) ?
+                             (*(pixel_row_ptr + index_w * stride_w + (index_h + 1) * stride_h)) :
+                             const_border_value;
+            const auto a11 = (-1 <= index_w && index_w < in_dim_w - 1 && -1 <= index_h && index_h < in_dim_h - 1) ?
+                             (*(pixel_row_ptr + (index_w + 1) * stride_w + (index_h + 1) * stride_h)) :
+                             const_border_value;
+
+            const float inp00                   = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info);
+            const float inp01                   = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info);
+            const float inp10                   = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info);
+            const float inp11                   = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info);
+            *reinterpret_cast<T *>(dst_i.ptr()) = Qasymm8QuantizationHelper<T>::quantize(scale_helpers::delta_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info);
+        },
+        src_i, dst_i);
+    }
+    else if(_border_mode == BorderMode::REPLICATE)
+    {
+        execute_window_loop(window, [&](const Coordinates & id)
+        {
+            const int     index_h       = std::floor((id[idx_height] + _sampling_offset) * hr - _sampling_offset);
+            const int32_t index_w       = *(reinterpret_cast<const int32_t *>(offsets->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
+            const auto    dx_val        = *(reinterpret_cast<const float *>(dx->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
+            const auto    dy_val        = *(reinterpret_cast<const float *>(dy->ptr_to_element(Coordinates(id[idx_width], id[idx_height]))));
+            const auto    pixel_row_ptr = reinterpret_cast<const T *>(src_i.ptr());
+
+            auto clamped_w  = utility::clamp<int>(index_w, 0, in_dim_w - 1);
+            auto clamped_w1 = utility::clamp<int>(index_w + 1, 0, in_dim_w - 1);
+            auto clamped_h  = utility::clamp<int>(index_h, 0, in_dim_h - 1);
+            auto clamped_h1 = utility::clamp<int>(index_h + 1, 0, in_dim_h - 1);
+
+            const auto a00 = *(pixel_row_ptr + clamped_w * stride_w + clamped_h * stride_h);
+            const auto a01 = *(pixel_row_ptr + clamped_w1 * stride_w + clamped_h * stride_h);
+            const auto a10 = *(pixel_row_ptr + clamped_w * stride_w + clamped_h1 * stride_h);
+            const auto a11 = *(pixel_row_ptr + clamped_w1 * stride_w + clamped_h1 * stride_h);
+
+            const float inp00                   = Qasymm8QuantizationHelper<T>::dequantize(a00, iq_info);
+            const float inp01                   = Qasymm8QuantizationHelper<T>::dequantize(a01, iq_info);
+            const float inp10                   = Qasymm8QuantizationHelper<T>::dequantize(a10, iq_info);
+            const float inp11                   = Qasymm8QuantizationHelper<T>::dequantize(a11, iq_info);
+            *reinterpret_cast<T *>(dst_i.ptr()) = Qasymm8QuantizationHelper<T>::quantize(scale_helpers::delta_bilinear(inp00, inp01, inp10, inp11, dx_val, dy_val), oq_info);
+        },
+        src_i, dst_i);
+    }
+    else
+    {
+        ARM_COMPUTE_ERROR("Not implemented");
+    }
+}
+#endif // ENABLE_NCHW_KERNELS
+
+Status CpuScaleKernel::validate(const ITensorInfo *input, const ITensorInfo *dx, const ITensorInfo *dy,
+                                const ITensorInfo *offsets, ITensorInfo *output, const ScaleKernelInfo &info)
+{
+    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, dx, dy, offsets, output, info));
+    return Status{};
+}
+
+void CpuScaleKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info)
+{
+    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICpuKernel::window(), window);
+    ARM_COMPUTE_ERROR_ON(_func == nullptr && _data_layout == DataLayout::NCHW);
+    ARM_COMPUTE_ERROR_ON(_run_method == nullptr && _data_layout == DataLayout::NHWC);
+
+    const auto src     = tensors.get_const_tensor(TensorType::ACL_SRC);
+    auto       dst     = tensors.get_tensor(TensorType::ACL_DST);
+    const auto dx      = tensors.get_const_tensor(TensorType::ACL_INT_0);
+    const auto dy      = tensors.get_const_tensor(TensorType::ACL_INT_1);
+    const auto offsets = tensors.get_const_tensor(TensorType::ACL_INT_2);
+
+    if(_data_layout == DataLayout::NCHW)
+    {
+        (this->*_func)(src, dst, dx, dy, offsets, window);
+    }
+    else
+    {
+        _run_method(src, dst, offsets, dx, dy, _policy, _border_mode, _constant_border_value, _sampling_offset, _align_corners, window);
+    }
+}
+
+const char *CpuScaleKernel::name() const
+{
+    return _name.c_str();
+}
+} // namespace kernels
+} // namespace cpu
+} // namespace arm_compute