diff --git a/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_EfficientDet_Models.md b/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_EfficientDet_Models.md
index a0e6c2b6cf9..7f57895edbe 100644
--- a/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_EfficientDet_Models.md
+++ b/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_EfficientDet_Models.md
@@ -67,8 +67,15 @@ The attribute names are self-explanatory or match the name in the `hparams_confi
 
 > **NOTE**: The color channel order (RGB or BGR) of an input data should match the channel order of the model training dataset. If they are different, perform the `RGB<->BGR` conversion specifying the command-line parameter: `--reverse_input_channels`. Otherwise, inference results may be incorrect. For more information about the parameter, refer to **When to Reverse Input Channels** section of [Converting a Model to Intermediate Representation (IR)](../Converting_Model.md).
 
-OpenVINO&trade; toolkit provides samples that can be used to infer EfficientDet model. For more information, refer to
-[Open Model Zoo Demos](@ref omz_demos) and
+## OpenVINO™ Toolkit Samples and Open Model Zoo Demos
+OpenVINO&trade; toolkit provides samples that can be used to infer EfficientDet models. For more information, refer to the following pages:
+* [OpenVINO Samples](../../../../OV_Runtime_UG/Samples_Overview.md)
+    * [Hello Reshape SSD - Python](../../../../../samples/python/hello_reshape_ssd/README.md)
+    * [Hello Reshape SSD - C++](../../../../../samples/cpp/hello_reshape_ssd/README.md)
+* [Open Model Zoo Demos](@ref omz_demos)
+    * [Object Detection Python Demo](https://github.com/openvinotoolkit/open_model_zoo/blob/master/demos/object_detection_demo/python)
+    * [Object Detection C++ Demo](https://github.com/openvinotoolkit/open_model_zoo/tree/master/demos/object_detection_demo/cpp)
+* [Hello Object Detection Jupyter notebook](https://docs.openvino.ai/latest/notebooks/004-hello-detection-with-output.html)
 
 ## <a name="efficientdet-ir-results-interpretation"></a>Interpreting Results of the TensorFlow Model and the IR
 
@@ -90,4 +97,4 @@ The output of the IR is a list of 7-element tuples: `[image_id, class_id, confid
 * `x_max` -- normalized `x` coordinate of the upper right corner of the detected object.
 * `y_max` -- normalized `y` coordinate of the upper right corner of the detected object.
 
-The first element with `image_id = -1` means end of data.
\ No newline at end of file
+The first element with `image_id = -1` means end of data.
diff --git a/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_Object_Detection_API_Models.md b/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_Object_Detection_API_Models.md
index b8276191219..8174b13c390 100644
--- a/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_Object_Detection_API_Models.md
+++ b/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_Object_Detection_API_Models.md
@@ -64,7 +64,11 @@ Speech Recognition, Natural Language Processing and others. Refer to the links b
 
 
 * [OpenVINO Samples](../../../../OV_Runtime_UG/Samples_Overview.md)
+    * [Hello Reshape SSD - Python](../../../../../samples/python/hello_reshape_ssd/README.md)
+    * [Hello Reshape SSD - C++](../../../../../samples/cpp/hello_reshape_ssd/README.md)
 * [Open Model Zoo Demos](@ref omz_demos)
+    * [Object Detection Python Demo](https://github.com/openvinotoolkit/open_model_zoo/blob/master/demos/object_detection_demo/python)
+    * [Object Detection C++ Demo](https://github.com/openvinotoolkit/open_model_zoo/tree/master/demos/object_detection_demo/cpp)
 
 ## Important Notes About Feeding Input Images to the Samples
 
diff --git a/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_YOLO_From_Tensorflow.md b/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_YOLO_From_Tensorflow.md
index 395745c26a9..e26515eca01 100644
--- a/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_YOLO_From_Tensorflow.md
+++ b/docs/MO_DG/prepare_model/convert_model/tf_specific/Convert_YOLO_From_Tensorflow.md
@@ -229,3 +229,10 @@ The model was trained with input values in the range `[0,1]`. OpenVINO&trade; to
 For other applicable parameters, refer to [Convert Model from TensorFlow](../Convert_Model_From_TensorFlow.md).
 
 > **NOTE**: The color channel order (RGB or BGR) of an input data should match the channel order of the model training dataset. If they are different, perform the `RGB<->BGR` conversion specifying the command-line parameter: `--reverse_input_channels`. Otherwise, inference results may be incorrect. For more information about the parameter, refer to **When to Reverse Input Channels** section of [Converting a Model to Intermediate Representation (IR)](../Converting_Model.md).
+
+
+<a name="yolo-examples"></a>
+## YOLO Sample Application
+OpenVINO™ [Open Model Zoo Demos](@ref omz_demos) provide a sample application showing how to run inferencing on a video input with object detection models. The sample is compatible with YOLOv1, YOLOv2, YOLOv3, and YOLOv4 full-size and tiny-size models:
+* [Object Detection Python Demo](https://github.com/openvinotoolkit/open_model_zoo/blob/master/demos/object_detection_demo/python)
+* [Object Detection C++ Demo](https://github.com/openvinotoolkit/open_model_zoo/tree/master/demos/object_detection_demo/cpp)