diff --git a/modules/dnn/src/onnx/onnx_importer.cpp b/modules/dnn/src/onnx/onnx_importer.cpp
index f6dc285fad..e65c7ac3e9 100644
--- a/modules/dnn/src/onnx/onnx_importer.cpp
+++ b/modules/dnn/src/onnx/onnx_importer.cpp
@@ -641,6 +641,17 @@ void ONNXImporter::populateNet(Net dstNet)
                     {
                         layerParams.type = "Scale";
                         layerParams.set("bias_term", true);
+                        int axis = 1;
+                        for (int i = 0; i < graph_proto.initializer_size(); i++)
+                        {
+                            opencv_onnx::TensorProto tensor_proto = graph_proto.initializer(i);
+                            if (tensor_proto.name() == node_proto.input(const_blob_id))
+                            {
+                                axis = inpShape.size() - tensor_proto.dims_size();
+                                break;
+                            }
+                        }
+                        layerParams.set("axis", axis);
                         blob = blob.reshape(1, 1);
                         layerParams.blobs.push_back((isSub ? -1 : 1) * blob);
                     }
@@ -911,13 +922,20 @@ void ONNXImporter::populateNet(Net dstNet)
             CV_Assert(node_proto.input_size() == 2);
             layerParams.type = "InnerProduct";
             layerParams.set("bias_term", false);
+            CV_Assert(constBlobs.find(node_proto.input(0)) == constBlobs.end());
+            int firstInpDims = outShapes[node_proto.input(0)].size();
+            int secondInpDims;
 
             if (constBlobs.find(node_proto.input(1)) != constBlobs.end())
             {
                 Mat blob = getBlob(node_proto, constBlobs, 1);
+                secondInpDims = blob.dims;
                 layerParams.blobs.push_back(blob.t());
                 layerParams.set("num_output", layerParams.blobs[0].size[0]);
+            } else {
+                secondInpDims = outShapes[node_proto.input(1)].size();
             }
+            layerParams.set("axis", firstInpDims - secondInpDims + 1);
         }
         else if (layer_type == "Mul" || layer_type == "Div")
         {
diff --git a/modules/dnn/test/test_onnx_importer.cpp b/modules/dnn/test/test_onnx_importer.cpp
index 6a9e68dbc5..a317be71fb 100644
--- a/modules/dnn/test/test_onnx_importer.cpp
+++ b/modules/dnn/test/test_onnx_importer.cpp
@@ -404,6 +404,15 @@ TEST_P(Test_ONNX_layers, MatMul)
     testONNXModels("matmul_4d");
 }
 
+TEST_P(Test_ONNX_layers, MatMulAdd)
+{
+    if (backend == DNN_BACKEND_INFERENCE_ENGINE_NN_BUILDER_2019)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_IE_NN_BUILDER);
+    if (backend == DNN_BACKEND_OPENCV && target == DNN_TARGET_OPENCL_FP16)
+        applyTestTag(CV_TEST_TAG_DNN_SKIP_OPENCL_FP16);
+    testONNXModels("matmul_add");
+}
+
 TEST_P(Test_ONNX_layers, Expand)
 {
     testONNXModels("expand_batch");