diff --git a/modules/dnn/src/layers/convolution_layer.cpp b/modules/dnn/src/layers/convolution_layer.cpp
index 60611b52b2..453892ec45 100644
--- a/modules/dnn/src/layers/convolution_layer.cpp
+++ b/modules/dnn/src/layers/convolution_layer.cpp
@@ -1217,12 +1217,8 @@ public:
         int dims[] = {inputs[0][0], outCn, outH, outW};
         outputs.resize(inputs.size(), shape(dims, 4));
 
-        internals.push_back(MatShape());
         if (!is1x1())
-            internals[0] = computeColRowShape(inputs[0], outputs[0]);
-
-        if (hasBias())
-            internals.push_back(shape(1, outH*outW));
+            internals.push_back(computeColRowShape(inputs[0], outputs[0]));
 
         return false;
     }
diff --git a/modules/dnn/src/onnx/onnx_importer.cpp b/modules/dnn/src/onnx/onnx_importer.cpp
index 218775b39f..b2c347f820 100644
--- a/modules/dnn/src/onnx/onnx_importer.cpp
+++ b/modules/dnn/src/onnx/onnx_importer.cpp
@@ -584,7 +584,7 @@ void ONNXImporter::populateNet(Net dstNet)
             for (int j = 1; j < node_proto.input_size(); j++) {
                 layerParams.blobs.push_back(getBlob(node_proto, constBlobs, j));
             }
-            layerParams.set("num_output", layerParams.blobs[0].size[1]);
+            layerParams.set("num_output", layerParams.blobs[0].size[1] * layerParams.get<int>("group", 1));
             layerParams.set("bias_term", node_proto.input_size() == 3);
         }
         else if (layer_type == "Transpose")
diff --git a/modules/dnn/test/test_onnx_importer.cpp b/modules/dnn/test/test_onnx_importer.cpp
index 217ef34421..5bd517433f 100644
--- a/modules/dnn/test/test_onnx_importer.cpp
+++ b/modules/dnn/test/test_onnx_importer.cpp
@@ -72,6 +72,7 @@ TEST_P(Test_ONNX_layers, Deconvolution)
 {
     testONNXModels("deconvolution");
     testONNXModels("two_deconvolution");
+    testONNXModels("deconvolution_group");
 }
 
 TEST_P(Test_ONNX_layers, Dropout)