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diff --git a/tests/validation/fixtures/NonMaxSuppressionFixture.h b/tests/validation/fixtures/NonMaxSuppressionFixture.h
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+/*
+ * Copyright (c) 2019 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.
+ */
+#ifndef ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE
+#define ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE
+
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorShape.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/Tensor.h"
+#include "tests/AssetsLibrary.h"
+#include "tests/Globals.h"
+#include "tests/IAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Fixture.h"
+#include "tests/validation/reference/NonMaxSuppression.h"
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+template <typename TensorType, typename AccessorType, typename FunctionType>
+
+class NMSValidationFixture : public framework::Fixture
+{
+public:
+    template <typename...>
+    void setup(TensorShape input_shape, unsigned int max_output_size, float score_threshold, float nms_threshold)
+    {
+        ARM_COMPUTE_ERROR_ON(max_output_size == 0);
+        ARM_COMPUTE_ERROR_ON(input_shape.num_dimensions() != 2);
+        const TensorShape output_shape(max_output_size);
+        const TensorShape scores_shape(input_shape[1]);
+        _target    = compute_target(input_shape, scores_shape, output_shape, max_output_size, score_threshold, nms_threshold);
+        _reference = compute_reference(input_shape, scores_shape, output_shape, max_output_size, score_threshold, nms_threshold);
+    }
+
+protected:
+    template <typename U>
+    void fill(U &&tensor, int i, int lo, int hi)
+    {
+        std::uniform_real_distribution<> distribution(lo, hi);
+        library->fill_boxes(tensor, distribution, i);
+    }
+
+    TensorType compute_target(const TensorShape input_shape, const TensorShape scores_shape, const TensorShape output_shape,
+                              unsigned int max_output_size, float score_threshold, float nms_threshold)
+    {
+        // Create tensors
+        TensorType bboxes  = create_tensor<TensorType>(input_shape, DataType::F32);
+        TensorType scores  = create_tensor<TensorType>(scores_shape, DataType::F32);
+        TensorType indices = create_tensor<TensorType>(output_shape, DataType::S32);
+
+        // Create and configure function
+        FunctionType nms_func;
+        nms_func.configure(&bboxes, &scores, &indices, max_output_size, score_threshold, nms_threshold);
+
+        ARM_COMPUTE_EXPECT(bboxes.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(indices.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(scores.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Allocate tensors
+        bboxes.allocator()->allocate();
+        indices.allocator()->allocate();
+        scores.allocator()->allocate();
+
+        ARM_COMPUTE_EXPECT(!bboxes.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!indices.info()->is_resizable(), framework::LogLevel::ERRORS);
+        ARM_COMPUTE_EXPECT(!scores.info()->is_resizable(), framework::LogLevel::ERRORS);
+
+        // Fill tensors
+        fill(AccessorType(bboxes), 0, 0.f, 1.f);
+        fill(AccessorType(scores), 1, 0.f, 1.f);
+
+        // Compute function
+        nms_func.run();
+        return indices;
+    }
+
+    SimpleTensor<int> compute_reference(const TensorShape input_shape, const TensorShape scores_shape, const TensorShape output_shape,
+                                        unsigned int max_output_size, float score_threshold, float nms_threshold)
+    {
+        // Create reference
+        SimpleTensor<float> bboxes{ input_shape, DataType::F32 };
+        SimpleTensor<float> scores{ scores_shape, DataType::F32 };
+        SimpleTensor<int>   indices{ output_shape, DataType::S32 };
+
+        // Fill reference
+        fill(bboxes, 0, 0.f, 1.f);
+        fill(scores, 1, 0.f, 1.f);
+
+        return reference::non_max_suppression(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold);
+    }
+
+    TensorType        _target{};
+    SimpleTensor<int> _reference{};
+};
+
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* ARM_COMPUTE_TEST_NON_MAX_SUPPRESSION_FIXTURE */