diff --git a/modules/dnn/src/layers/concat_layer.cpp b/modules/dnn/src/layers/concat_layer.cpp
index ecd6ff29a8..a0453842e4 100644
--- a/modules/dnn/src/layers/concat_layer.cpp
+++ b/modules/dnn/src/layers/concat_layer.cpp
@@ -108,7 +108,10 @@ public:
                 }
             }
 
-            axisSum += curShape[cAxis];
+            axisSum += (!curShape.empty()) ? curShape[cAxis] : 1;
+        }
+        if (inputs[0].empty()){
+            outputs[0] = MatShape(1);
         }
         outputs[0][cAxis] = axisSum;
         return false;
diff --git a/modules/dnn/test/test_layers_1d.cpp b/modules/dnn/test/test_layers_1d.cpp
index 097bce1ecd..16cb2836fe 100644
--- a/modules/dnn/test/test_layers_1d.cpp
+++ b/modules/dnn/test/test_layers_1d.cpp
@@ -349,4 +349,36 @@ INSTANTIATE_TEST_CASE_P(/*nothing*/, Layer_Expand_Test, Combine(
     )
 ));
 
+typedef testing::TestWithParam<tuple<std::vector<int>>> Layer_Concat_Test;
+TEST_P(Layer_Concat_Test, Accuracy_01D)
+{
+    LayerParams lp;
+    lp.type = "Concat";
+    lp.name = "ConcatLayer";
+    lp.set("axis", 0);
+
+    Ptr<ConcatLayer> layer = ConcatLayer::create(lp);
+
+    std::vector<int> input_shape = get<0>(GetParam());
+    std::vector<int> output_shape = {3};
+
+    Mat input1(input_shape.size(), input_shape.data(), CV_32F, 1.0);
+    Mat input2(input_shape.size(), input_shape.data(), CV_32F, 2.0);
+    Mat input3(input_shape.size(), input_shape.data(), CV_32F, 3.0);
+
+    float data[] = {1.0, 2.0, 3.0};
+    Mat output_ref(output_shape, CV_32F, data);
+
+    std::vector<Mat> inputs{input1, input2, input3};
+    std::vector<Mat> outputs;
+
+    runLayer(layer, inputs, outputs);
+    ASSERT_EQ(shape(output_ref), shape(outputs[0]));
+    normAssert(output_ref, outputs[0]);
+}
+INSTANTIATE_TEST_CASE_P(/*nothing*/, Layer_Concat_Test,
+/*input blob shape*/    testing::Values(
+    std::vector<int>({}),
+    std::vector<int>({1})
+));
 }}