diff --git a/modules/dnn/src/darknet/darknet_io.cpp b/modules/dnn/src/darknet/darknet_io.cpp
index ff322bc188..405209c458 100644
--- a/modules/dnn/src/darknet/darknet_io.cpp
+++ b/modules/dnn/src/darknet/darknet_io.cpp
@@ -229,6 +229,10 @@ namespace cv {
                     {
                         activation_param.type = "Swish";
                     }
+                    else if (type == "mish")
+                    {
+                        activation_param.type = "Mish";
+                    }
                     else if (type == "logistic")
                     {
                         activation_param.type = "Sigmoid";
@@ -436,7 +440,7 @@ namespace cv {
                     fused_layer_names.push_back(last_layer);
                 }
 
-                void setYolo(int classes, const std::vector<int>& mask, const std::vector<float>& anchors, float thresh, float nms_threshold)
+                void setYolo(int classes, const std::vector<int>& mask, const std::vector<float>& anchors, float thresh, float nms_threshold, float scale_x_y)
                 {
                     cv::dnn::LayerParams region_param;
                     region_param.name = "Region-name";
@@ -449,6 +453,7 @@ namespace cv {
                     region_param.set<bool>("logistic", true);
                     region_param.set<float>("thresh", thresh);
                     region_param.set<float>("nms_threshold", nms_threshold);
+                    region_param.set<float>("scale_x_y", scale_x_y);
 
                     std::vector<float> usedAnchors(numAnchors * 2);
                     for (int i = 0; i < numAnchors; ++i)
@@ -786,6 +791,7 @@ namespace cv {
                         int num_of_anchors = getParam<int>(layer_params, "num", -1);
                         float thresh = getParam<float>(layer_params, "thresh", 0.2);
                         float nms_threshold = getParam<float>(layer_params, "nms_threshold", 0.4);
+                        float scale_x_y = getParam<float>(layer_params, "scale_x_y", 1.0);
 
                         std::string anchors_values = getParam<std::string>(layer_params, "anchors", std::string());
                         CV_Assert(!anchors_values.empty());
@@ -798,7 +804,7 @@ namespace cv {
                         CV_Assert(classes > 0 && num_of_anchors > 0 && (num_of_anchors * 2) == anchors_vec.size());
 
                         setParams.setPermute(false);
-                        setParams.setYolo(classes, mask_vec, anchors_vec, thresh, nms_threshold);
+                        setParams.setYolo(classes, mask_vec, anchors_vec, thresh, nms_threshold, scale_x_y);
                     }
                     else {
                         CV_Error(cv::Error::StsParseError, "Unknown layer type: " + layer_type);
@@ -813,6 +819,10 @@ namespace cv {
                     {
                         setParams.setActivation("swish");
                     }
+                    else if (activation == "mish")
+                    {
+                        setParams.setActivation("mish");
+                    }
                     else if (activation == "logistic")
                     {
                         setParams.setActivation("logistic");
@@ -935,8 +945,8 @@ namespace cv {
                     }
 
                     std::string activation = getParam<std::string>(layer_params, "activation", "linear");
-                    if(activation == "leaky" || activation == "swish" || activation == "logistic")
-                        ++cv_layers_counter;  // For ReLU, Swish, Sigmoid
+                    if(activation == "leaky" || activation == "swish" || activation == "mish" || activation == "logistic")
+                        ++cv_layers_counter;  // For ReLU, Swish, Mish, Sigmoid
 
                     if(!darknet_layers_counter)
                         tensor_shape.resize(1);
diff --git a/modules/dnn/src/layers/region_layer.cpp b/modules/dnn/src/layers/region_layer.cpp
index e2a0733652..d229369abb 100644
--- a/modules/dnn/src/layers/region_layer.cpp
+++ b/modules/dnn/src/layers/region_layer.cpp
@@ -63,7 +63,7 @@ class RegionLayerImpl CV_FINAL : public RegionLayer
 {
 public:
     int coords, classes, anchors, classfix;
-    float thresh, nmsThreshold;
+    float thresh, nmsThreshold, scale_x_y;
     bool useSoftmax, useLogistic;
 #ifdef HAVE_OPENCL
     UMat blob_umat;
@@ -82,6 +82,7 @@ public:
         useSoftmax = params.get<bool>("softmax", false);
         useLogistic = params.get<bool>("logistic", false);
         nmsThreshold = params.get<float>("nms_threshold", 0.4);
+        scale_x_y = params.get<float>("scale_x_y", 1.0); // Yolov4
 
         CV_Assert(nmsThreshold >= 0.);
         CV_Assert(coords == 4);
@@ -292,8 +293,10 @@ public:
                             if (classfix == -1 && scale < .5) scale = 0;  // if(t0 < 0.5) t0 = 0;
                             int box_index = index_sample_offset + index * cell_size;
 
-                            dstData[box_index + 0] = (x + logistic_activate(srcData[box_index + 0])) / cols;
-                            dstData[box_index + 1] = (y + logistic_activate(srcData[box_index + 1])) / rows;
+                            float x_tmp = (logistic_activate(srcData[box_index + 0]) - 0.5f) * scale_x_y + 0.5f;
+                            float y_tmp = (logistic_activate(srcData[box_index + 1]) - 0.5f) * scale_x_y + 0.5f;
+                            dstData[box_index + 0] = (x + x_tmp) / cols;
+                            dstData[box_index + 1] = (y + y_tmp) / rows;
                             dstData[box_index + 2] = exp(srcData[box_index + 2]) * biasData[2 * a] / wNorm;
                             dstData[box_index + 3] = exp(srcData[box_index + 3]) * biasData[2 * a + 1] / hNorm;
 
@@ -406,6 +409,8 @@ public:
         auto shape_3d = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{boxes_shape.size()}, boxes_shape.data());
 
         ngraph::Shape box_broad_shape{1, (size_t)anchors, (size_t)h, (size_t)w};
+        auto scale_x_y_node = std::make_shared<ngraph::op::Constant>(ngraph::element::f32, ngraph::Shape{1}, &scale_x_y);
+        auto shift_node = std::make_shared<ngraph::op::Constant>(ngraph::element::f32, ngraph::Shape{1}, std::vector<float>{0.5});
 
         std::shared_ptr<ngraph::Node> box_x;
         {
@@ -413,6 +418,9 @@ public:
             auto upper_bounds = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{2}, std::vector<int64_t>{1, cols});
             box_x = std::make_shared<ngraph::op::v1::StridedSlice>(input2d, lower_bounds, upper_bounds, strides, std::vector<int64_t>{}, std::vector<int64_t>{});
             box_x = std::make_shared<ngraph::op::Sigmoid>(box_x);
+            box_x = std::make_shared<ngraph::op::v1::Subtract>(box_x, shift_node, ngraph::op::AutoBroadcastType::NUMPY);
+            box_x = std::make_shared<ngraph::op::v1::Multiply>(box_x, scale_x_y_node, ngraph::op::AutoBroadcastType::NUMPY);
+            box_x = std::make_shared<ngraph::op::v1::Add>(box_x, shift_node, ngraph::op::AutoBroadcastType::NUMPY);
             box_x = std::make_shared<ngraph::op::v1::Reshape>(box_x, shape_3d, true);
 
             std::vector<float> x_indices(w * h * anchors);
@@ -439,6 +447,9 @@ public:
             auto upper_bounds = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{2}, std::vector<int64_t>{2, cols});
             box_y = std::make_shared<ngraph::op::v1::StridedSlice>(input2d, lower_bounds, upper_bounds, strides, std::vector<int64_t>{}, std::vector<int64_t>{});
             box_y = std::make_shared<ngraph::op::Sigmoid>(box_y);
+            box_y = std::make_shared<ngraph::op::v1::Subtract>(box_y, shift_node, ngraph::op::AutoBroadcastType::NUMPY);
+            box_y = std::make_shared<ngraph::op::v1::Multiply>(box_y, scale_x_y_node, ngraph::op::AutoBroadcastType::NUMPY);
+            box_y = std::make_shared<ngraph::op::v1::Add>(box_y, shift_node, ngraph::op::AutoBroadcastType::NUMPY);
             box_y = std::make_shared<ngraph::op::v1::Reshape>(box_y, shape_3d, true);
 
             std::vector<float> y_indices(h * anchors);
diff --git a/modules/dnn/test/test_darknet_importer.cpp b/modules/dnn/test/test_darknet_importer.cpp
index e76c16e273..de5ff7f0c4 100644
--- a/modules/dnn/test/test_darknet_importer.cpp
+++ b/modules/dnn/test/test_darknet_importer.cpp
@@ -523,6 +523,11 @@ TEST_P(Test_Darknet_layers, upsample)
     testDarknetLayer("upsample");
 }
 
+TEST_P(Test_Darknet_layers, mish)
+{
+    testDarknetLayer("mish", true);
+}
+
 TEST_P(Test_Darknet_layers, avgpool_softmax)
 {
     testDarknetLayer("avgpool_softmax");