diff --git a/docs/source/guide/explanation/algorithms/object_detection/object_detection.rst b/docs/source/guide/explanation/algorithms/object_detection/object_detection.rst
index 1cf89b52c5b..b744f255537 100644
--- a/docs/source/guide/explanation/algorithms/object_detection/object_detection.rst
+++ b/docs/source/guide/explanation/algorithms/object_detection/object_detection.rst
@@ -71,51 +71,82 @@ Models
 
 We support the following ready-to-use model templates:
 
-+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------+---------------------+-----------------+
-| Template ID                                                                                                                                                                               | Name    | Complexity (GFLOPs) | Model size (MB) |
-+===========================================================================================================================================================================================+=========+=====================+=================+
-| `Custom_Object_Detection_YOLOX <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/cspdarknet_yolox/template.yaml>`_      | YOLOX   | 6.5                 | 20.4            |
-+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------+---------------------+-----------------+
-| `Custom_Object_Detection_Gen3_SSD <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/mobilenetv2_ssd/template.yaml>`_    | SSD     | 9.4                 | 7.6             |
-+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------+---------------------+-----------------+
-| `Custom_Object_Detection_Gen3_ATSS <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml>`_  | ATSS    | 20.6                | 9.1             |
-+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------+---------------------+-----------------+
-
-`ATSS <https://arxiv.org/abs/1912.02424>`_ is a good medium-range model that works well and fast in most cases.
++-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+| Template ID                                                                                                                                                                               | Name                | Complexity (GFLOPs) | Model size (MB) |
++===========================================================================================================================================================================================+=====================+=====================+=================+
+| `Custom_Object_Detection_YOLOX <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/cspdarknet_yolox/template.yaml>`_      |        YOLOX        | 6.5                 | 20.4            |
++-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+| `Custom_Object_Detection_Gen3_SSD <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/mobilenetv2_ssd/template.yaml>`_    |         SSD         | 9.4                 | 7.6             |
++-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+| `Custom_Object_Detection_Gen3_ATSS <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml>`_  |  MobileNetV2-ATSS   | 20.6                | 9.1             |
++-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+
+Above table can be found using the following command
+
+.. code-block::
+    $ otx find --task detection
+
+`MobileNetV2-ATSS <https://arxiv.org/abs/1912.02424>`_ is a good medium-range model that works well and fast in most cases.
 `SSD <https://arxiv.org/abs/1512.02325>`_ and `YOLOX <https://arxiv.org/abs/2107.08430>`_ are light models, that a perfect for the fastest inference on low-power hardware.
 YOLOX achieved the same accuracy as SSD, and even outperforms its inference on CPU 1.5 times, but requires 3 times more time for training due to `Mosaic augmentation <https://arxiv.org/pdf/2004.10934.pdf>`_, which is even more than for ATSS.
 So if you have resources for a long training, you can pick the YOLOX model.
 
+In addition to these models, we supports experimental models for object detection. These experimental models will be changed to official models within a few releases.
+
++---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+| Template ID                                                                                                                                                                                                               | Name                | Complexity (GFLOPs) | Model size (MB) |
++===========================================================================================================================================================================================================================+=====================+=====================+=================+
+| `Custom_Object_Detection_Gen3_Deformable_DETR <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/resnet50_deformable_detr/template_experimental.yaml>`_  |   Deformable_DETR   | 165                 | 157.0           |
++---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+| `Custom_Object_Detection_Gen3_DINO <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/resnet50_dino/template_experimental.yaml>`_                        |        DINO         | 235                 | 182.0           |
++---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+| `Custom_Object_Detection_Gen3_ResNeXt101_ATSS <https://github.com/openvinotoolkit/training_extensions/blob/develop/src/otx/algorithms/detection/configs/detection/resnext101_atss/template_experimental.yaml>`_           |   ResNeXt101-ATSS   | 434.75              | 344.0           |
++---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+---------------------+---------------------+-----------------+
+
+`Deformable_DETR <https://arxiv.org/abs/2010.04159>`_ is `DETR <https://arxiv.org/abs/2005.12872>`_ based model, and it solves slow convergence problem of DETR. `DINO <https://arxiv.org/abs/2203.03605>`_ improves Deformable DETR based methods via denoising anchor boxes. Current SOTA models for object detection are based on DINO. 
+Although transformer based models show notable performance on various object detection benchmark, CNN based model still show good performance with proper latency.
+Therefore, we added a new experimental CNN based method, ResNeXt101-ATSS. ATSS still shows good performance among `RetinaNet <https://arxiv.org/abs/1708.02002>`_ based models. We integrated large ResNeXt101 backbone to our Custom ATSS head, and it shows good transfer learning performance.
+
+.. note::
+
+    For using experimental templates, you should specify full path of experimental template. Ex) otx build src/otx/algorithms/detection/configs/detection/resnet50_dino/template_experimental.yaml --task detection
+
 Besides this, we support public backbones from `torchvision <https://pytorch.org/vision/stable/index.html>`_, `pytorchcv <https://github.com/osmr/imgclsmob>`_, `mmcls <https://github.com/open-mmlab/mmclassification>`_ and `OpenVino Model Zoo <https://github.com/openvinotoolkit/open_model_zoo>`_.
 Please, refer to the :doc:`tutorial <../../../tutorials/advanced/backbones>` how to customize models and run public backbones.
 
 To see which public backbones are available for the task, the following command can be executed:
 
 .. code-block::
-
-        $ otx find --backbone {torchvision, pytorchcv, mmcls, omz.mmcls}
+    $ otx find --backbone {torchvision, pytorchcv, mmcls, omz.mmcls}
 
 In the table below the test mAP on some academic datasets using our :ref:`supervised pipeline <od_supervised_pipeline>` is presented.
 
-For `COCO <https://cocodataset.org/#home>`__ dataset the accuracy of pretrained weights is shown. That means that weights are undertrained for COCO dataset and don't achieve the best result.
-That is because the purpose of pretrained models is to learn basic features from a such large and diverse dataset as COCO and to use these weights to get good results for other custom datasets right from the start.
+For `COCO <https://cocodataset.org/#home>`__ dataset the accuracy of pretrained weights is shown, and we report official COCO mAP with AP50. 
+Except for COCO, we report AP50 as performance metric.
 
-The results on `Pascal VOC <http://host.robots.ox.ac.uk/pascal/VOC/voc2012/>`_,  `BCCD <https://public.roboflow.com/object-detection/bccd/3>`_, `MinneApple <https://rsn.umn.edu/projects/orchard-monitoring/minneapple>`_ and `WGISD <https://github.com/thsant/wgisd>`_  were obtained on our templates without any changes.
-BCCD is an easy dataset with focused large objects, while MinneApple and WGISD have small objects that are hard to distinguish from the background.
+5 datasets were selected as transfer learning datasets. 
+`BDD100K <https://www.bdd100k.com/>`_ is the largest dataset among we used. 70000 images are used as train images and 10000 images are used for validation.
+`Brackish <https://public.roboflow.com/object-detection/brackish-underwater>`_ and `Plantdoc <https://public.roboflow.com/object-detection/plantdoc>`_ are datasets of medium size. They have around 10000 images for train and 1500 images for validation.
+`BCCD <https://public.roboflow.com/object-detection/bccd>`_ and `Chess pieces <https://public.roboflow.com/object-detection/chess-full>`_ are datasets of small size. They have around 300 images for train and 100 images for validation.
+We used our own templates without any modification.
 For hyperparameters, please, refer to the related template.
 We trained each model with a single Nvidia GeForce RTX3090.
 
-+-----------+------------+-----------+-----------+-----------+-----------+
-| Model name| COCO       | PASCAL VOC| BCCD      | MinneApple| WGISD     |
-+===========+============+===========+===========+===========+===========+
-| YOLOX     | 32.0       | 66.6      | 60.3      | 24.5      | 44.1      |
-+-----------+------------+-----------+-----------+-----------+-----------+
-| SSD       | 13.5       | 50.0      | 54.2      | 31.2      | 45.9      |
-+-----------+------------+-----------+-----------+-----------+-----------+
-| ATSS      | 32.5       | 68.7      | 61.5      | 42.5      | 57.5      |
-+-----------+------------+-----------+-----------+-----------+-----------+
-
-
++----------------------------+------------------+-----------+-----------+-----------+-----------+--------------+
+| Model name                 | COCO(AP50)       | BDD100K   | Brackish  | Plantdoc  | BCCD      | Chess pieces |
++============================+==================+===========+===========+===========+===========+==============+
+| YOLOX                      | 31.0 (48.2)      | 24.8      | 96.3      | 51.5      | 88.5      | 99.2         |
++----------------------------+------------------+-----------+-----------+-----------+-----------+--------------+
+| SSD                        | 13.5             | 28.2      | 96.5      | 52.9      | 91.1      | 99.1         |
++----------------------------+------------------+-----------+-----------+-----------+-----------+--------------+
+| MobileNetV2-ATSS           | 32.5 (49.5)      | 40.2      | 99.1      | 63.4      | 93.4      | 99.1         |
++----------------------------+------------------+-----------+-----------+-----------+-----------+--------------+
+| ResNeXt101-ATSS            | 45.1 (63.8)      | 45.5      | 99.3      | 69.3      | 93.1      | 99.1         |
++----------------------------+------------------+-----------+-----------+-----------+-----------+--------------+
+| ResNet50-Deformable-DETR   | 44.3 (63.2)      | 44.8      | 97.7      | 60.7      | 93.4      | 99.2         |
++----------------------------+------------------+-----------+-----------+-----------+-----------+--------------+
+| ResNet50-DINO              | 49.0 (66.4)      | 47.2      | 99.5      | 62.9      | 93.5      | 99.1         |
++----------------------------+------------------+-----------+-----------+-----------+-----------+--------------+
 
 ************************
 Semi-supervised Learning
@@ -142,26 +173,26 @@ In the table below the mAP on toy data sample from `COCO <https://cocodataset.or
 
 We sample 400 images that contain one of [person, car, bus] for labeled train images. And 4000 images for unlabeled images. For validation 100 images are selected from val2017.
 
-+---------+--------------------------------------------+
-| Dataset |            Sampled COCO dataset            |
-+=========+=====================+======================+
-|         |          SL         |       Semi-SL        |
-+---------+---------------------+----------------------+
-|  ATSS   |  | Person: 69.70    | | Person: 69.44      |
-|         |  | Car:    65.00    | | Car:    65.84      |
-|         |  | Bus:    42.96    | | Bus:    50.7       |
-|         |  | Mean:   59.20    | | Mean:   61.98      |
-+---------+---------------------+----------------------+
-|   SSD   | | Person: 39.24     | | Person: 38.52      |
-|         | | Car:    19.24     | | Car:    28.02      |
-|         | | Bus:    21.34     | | Bus:    26.28      |
-|         | | Mean:   26.60     | | Mean:   30.96      |
-+---------+---------------------+----------------------+
-|  YOLOX  | | Person: 65.64     | | Person: 69.00      |
-|         | | Car:    64.44     | | Car:   65.66       |
-|         | | Bus:    60.68     | | Bus:   65.12       |
-|         | | Mean:   63.6      | | Mean:  66.58       |
-+---------+---------------------+----------------------+
++---------------------+--------------------------------------------+
+| Dataset             |            Sampled COCO dataset            |
++=====================+=====================+======================+
+|                     |          SL         |       Semi-SL        |
++---------------------+---------------------+----------------------+
+|  MobileNetV2-ATSS   |  | Person: 69.70    | | Person: 69.44      |
+|                     |  | Car:    65.00    | | Car:    65.84      |
+|                     |  | Bus:    42.96    | | Bus:    50.7       |
+|                     |  | Mean:   59.20    | | Mean:   61.98      |
++---------------------+---------------------+----------------------+
+|   SSD               | | Person: 39.24     | | Person: 38.52      |
+|                     | | Car:    19.24     | | Car:    28.02      |
+|                     | | Bus:    21.34     | | Bus:    26.28      |
+|                     | | Mean:   26.60     | | Mean:   30.96      |
++---------------------+---------------------+----------------------+
+|  YOLOX              | | Person: 65.64     | | Person: 69.00      |
+|                     | | Car:    64.44     | | Car:   65.66       |
+|                     | | Bus:    60.68     | | Bus:   65.12       |
+|                     | | Mean:   63.6      | | Mean:  66.58       |
++---------------------+---------------------+----------------------+
 
 .. ************************
 .. Self-supervised Learning
diff --git a/docs/source/guide/get_started/cli_commands.rst b/docs/source/guide/get_started/cli_commands.rst
index e0700d38d4d..a177388d27f 100644
--- a/docs/source/guide/get_started/cli_commands.rst
+++ b/docs/source/guide/get_started/cli_commands.rst
@@ -32,13 +32,13 @@ Example to find ready-to-use templates for the detection task:
 .. code-block::
 
     (otx) ...$ otx find --task detection
-    +-----------+-----------------------------------+-------+-------------------------------------------------------------------------------+
-    |    TASK   |                 ID                |  NAME |                                   BASE PATH                                   |
-    +-----------+-----------------------------------+-------+-------------------------------------------------------------------------------+
-    | DETECTION | Custom_Object_Detection_Gen3_ATSS |  ATSS | src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml |
-    | DETECTION |  Custom_Object_Detection_Gen3_SSD |  SSD  | src/otx/algorithms/detection/configs/detection/mobilenetv2_ssd/template.yaml  |
-    | DETECTION |   Custom_Object_Detection_YOLOX   | YOLOX | src/otx/algorithms/detection/configs/detection/cspdarknet_yolox/template.yaml |
-    +-----------+-----------------------------------+-------+-------------------------------------------------------------------------------+
+    +-----------+-----------------------------------------------+------------------+-------------------------------------------------------------------------------+
+    |    TASK   |                       ID                      |       NAME       |                                   BASE PATH                                   |
+    +-----------+-----------------------------------------------+------------------+-------------------------------------------------------------------------------+
+    | DETECTION |        Custom_Object_Detection_Gen3_SSD       |       SSD        |  src/otx/algorithms/detection/configs/detection/mobilenetv2_ssd/template.yaml |
+    | DETECTION |         Custom_Object_Detection_YOLOX         |      YOLOX       | src/otx/algorithms/detection/configs/detection/cspdarknet_yolox/template.yaml |
+    | DETECTION |        Custom_Object_Detection_Gen3_ATSS      | MobileNetV2-ATSS | src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml |
+    +-----------+-----------------------------------------------+------------------+-------------------------------------------------------------------------------+
 
 
 Example to find supported torchvision backbones for the detection task:
diff --git a/docs/source/guide/tutorials/base/how_to_train/detection.rst b/docs/source/guide/tutorials/base/how_to_train/detection.rst
index af796a00402..dc36b7e66ab 100644
--- a/docs/source/guide/tutorials/base/how_to_train/detection.rst
+++ b/docs/source/guide/tutorials/base/how_to_train/detection.rst
@@ -134,13 +134,13 @@ The list of supported templates for object detection is available with the comma
 .. code-block::
 
   (otx) ...$ otx find --template --task DETECTION
-  +-----------+-----------------------------------+-------+-------------------------------------------------------------------------------+
-  |    TASK   |                 ID                |  NAME |                                      PATH                                     |
-  +-----------+-----------------------------------+-------+-------------------------------------------------------------------------------+
-  | DETECTION |   Custom_Object_Detection_YOLOX   | YOLOX | src/otx/algorithms/detection/configs/detection/cspdarknet_yolox/template.yaml |
-  | DETECTION |  Custom_Object_Detection_Gen3_SSD |  SSD  |  src/otx/algorithms/detection/configs/detection/mobilenetv2_ssd/template.yaml |
-  | DETECTION | Custom_Object_Detection_Gen3_ATSS |  ATSS | src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml |
-  +-----------+-----------------------------------+-------+-------------------------------------------------------------------------------+
+  +-----------+-----------------------------------------------+------------------+-------------------------------------------------------------------------------+
+  |    TASK   |                       ID                      |       NAME       |                                   BASE PATH                                   |
+  +-----------+-----------------------------------------------+------------------+-------------------------------------------------------------------------------+
+  | DETECTION |        Custom_Object_Detection_Gen3_SSD       |       SSD        |  src/otx/algorithms/detection/configs/detection/mobilenetv2_ssd/template.yaml |
+  | DETECTION |         Custom_Object_Detection_YOLOX         |      YOLOX       | src/otx/algorithms/detection/configs/detection/cspdarknet_yolox/template.yaml |
+  | DETECTION |        Custom_Object_Detection_Gen3_ATSS      | MobileNetV2-ATSS | src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml |
+  +-----------+-----------------------------------------------+------------------+-------------------------------------------------------------------------------+v
 
 .. _detection_workspace:
 
@@ -165,7 +165,7 @@ Let's prepare the object detection workspace running the following command:
   (otx) ...$ otx build Custom_Object_Detection_Gen3_ATSS --train-data-roots data/wgisd
 
   # or its name
-  (otx) ...$ otx build ATSS --train-data-roots data/wgisd
+  (otx) ...$ otx build MobileNetV2-ATSS --train-data-roots data/wgisd
 
   # or its path
   (otx) ...$ otx build otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml --train-data-roots data/wgisd
@@ -173,7 +173,7 @@ Let's prepare the object detection workspace running the following command:
   ...
   [*] Workspace Path: otx-workspace-DETECTION
   [*] Load Model Template ID: Custom_Object_Detection_Gen3_ATSS
-  [*] Load Model Name: ATSS
+  [*] Load Model Name: MobileNetV2-ATSS
   [*]     - Updated: otx-workspace-DETECTION/model.py
   [*]     - Updated: otx-workspace-DETECTION/data_pipeline.py
   [*]     - Updated: otx-workspace-DETECTION/tile_pipeline.py
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/__init__.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/__init__.py
index f410aa44375..a2e9b592e2f 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/__init__.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/__init__.py
@@ -1,4 +1,4 @@
-"""Initialization of ATSS model for Detection Task."""
+"""Initialization of MobileNetV2-ATSS model for Detection Task."""
 
 # Copyright (C) 2022 Intel Corporation
 #
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/data_pipeline.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/data_pipeline.py
index b159be5ef65..6417850cb24 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/data_pipeline.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/data_pipeline.py
@@ -1,4 +1,4 @@
-"""Data Pipeline of ATSS model for Detection Task."""
+"""Data Pipeline of MobileNetV2-ATSS model for Detection Task."""
 
 # Copyright (C) 2022 Intel Corporation
 #
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/deployment.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/deployment.py
index 2004bde9ef5..f716e4af3ba 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/deployment.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/deployment.py
@@ -1,4 +1,4 @@
-"""MMDeploy config of ATSS model for Detection Task."""
+"""MMDeploy config of MobileNetV2-ATSS model for Detection Task."""
 
 _base_ = ["../../base/deployments/base_detection_dynamic.py"]
 
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/model.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/model.py
index 0558e335d5b..6c9655789fd 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/model.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/model.py
@@ -1,4 +1,4 @@
-"""Model configuration of ATSS model for Detection Task."""
+"""Model configuration of MobileNetV2-ATSS model for Detection Task."""
 
 # Copyright (C) 2022 Intel Corporation
 #
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/__init__.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/__init__.py
index 150c670b2ac..117edfb950e 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/__init__.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/__init__.py
@@ -1,4 +1,4 @@
-"""Initialization of ATSS model for Semi-SL Detection Task."""
+"""Initialization of MobileNetV2-ATSS model for Semi-SL Detection Task."""
 
 # Copyright (C) 2022 Intel Corporation
 #
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/data_pipeline.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/data_pipeline.py
index faa0f1cfc77..e76301d6b14 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/data_pipeline.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/data_pipeline.py
@@ -1,4 +1,4 @@
-"""Data Pipeline of ATSS model for Semi-Supervised Learning Detection Task."""
+"""Data Pipeline of MobileNetV2-ATSS model for Semi-Supervised Learning Detection Task."""
 
 # Copyright (C) 2022 Intel Corporation
 #
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/model.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/model.py
index 3d0d9451a68..ddd79acf663 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/model.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/semisl/model.py
@@ -1,4 +1,4 @@
-"""Model configuration of ATSS model for Detection Task."""
+"""Model configuration of MobileNetV2-ATSS model for Detection Task."""
 
 # Copyright (C) 2022 Intel Corporation
 #
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml
index a5ad8133afc..04d1a2f6e60 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/template.yaml
@@ -1,10 +1,10 @@
 # Description.
 model_template_id: Custom_Object_Detection_Gen3_ATSS
-name: ATSS
+name: MobileNetV2-ATSS
 task_type: DETECTION
 task_family: VISION
 instantiation: "CLASS"
-summary: Class-Incremental Object Detection for ATSS
+summary: Class-Incremental Object Detection for MobileNetV2-ATSS
 application: ~
 
 # Algo backend.
diff --git a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/tile_pipeline.py b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/tile_pipeline.py
index 01a516d4b5c..c80d1cf2bed 100644
--- a/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/tile_pipeline.py
+++ b/src/otx/algorithms/detection/configs/detection/mobilenetv2_atss/tile_pipeline.py
@@ -1,4 +1,4 @@
-"""Tiling Pipeline of ATSS model for Detection Task."""
+"""Tiling Pipeline of MobileNetV2-ATSS model for Detection Task."""
 
 # Copyright (C) 2022 Intel Corporation
 #
diff --git a/tests/e2e/cli/detection/reference/Custom_Object_Detection_Gen3_ATSS/compressed_model.yml b/tests/e2e/cli/detection/reference/Custom_Object_Detection_Gen3_MobileNetV2_ATSS/compressed_model.yml
similarity index 100%
rename from tests/e2e/cli/detection/reference/Custom_Object_Detection_Gen3_ATSS/compressed_model.yml
rename to tests/e2e/cli/detection/reference/Custom_Object_Detection_Gen3_MobileNetV2_ATSS/compressed_model.yml
diff --git a/tests/e2e/test_api_xai_sanity.py b/tests/e2e/test_api_xai_sanity.py
index 2086c50f9da..8534276839e 100644
--- a/tests/e2e/test_api_xai_sanity.py
+++ b/tests/e2e/test_api_xai_sanity.py
@@ -147,7 +147,7 @@ def test_inference_xai(self, multilabel, hierarchical):
 
 class TestOVDetXAIAPI(DetectionTaskAPIBase):
     ref_raw_saliency_shapes = {
-        "ATSS": (6, 8),
+        "MobileNetV2-ATSS": (6, 8),
     }
 
     @e2e_pytest_api
@@ -216,7 +216,7 @@ def test_inference_xai(self):
 
 class TestOVDetTilXAIAPI(DetectionTaskAPIBase):
     ref_raw_saliency_shapes = {
-        "ATSS": (6, 8),
+        "MobileNetV2-ATSS": (6, 8),
     }
 
     @e2e_pytest_api
diff --git a/tests/integration/cli/test_cli.py b/tests/integration/cli/test_cli.py
index 6d471b3dbf2..0ab53438085 100644
--- a/tests/integration/cli/test_cli.py
+++ b/tests/integration/cli/test_cli.py
@@ -39,7 +39,12 @@
         "--model": "MobileNet-V3-large-1x",
         "--train-type": "Semisupervised",
     },
-    "detection": {"default": "ATSS", "--task": "detection", "--model": "SSD", "--train-type": "Semisupervised"},
+    "detection": {
+        "default": "MobileNetV2-ATSS",
+        "--task": "detection",
+        "--model": "SSD",
+        "--train-type": "Semisupervised",
+    },
 }
 
 
diff --git a/tests/regression/regression_config.json b/tests/regression/regression_config.json
index 3a931c121fc..823113ffb21 100644
--- a/tests/regression/regression_config.json
+++ b/tests/regression/regression_config.json
@@ -325,27 +325,27 @@
           "train": {
             "YOLOX": 0.537,
             "SSD": 0.179,
-            "ATSS": 0.446
+            "MobileNetV2-ATSS": 0.446
           },
           "export": {
             "YOLOX": 0.534,
             "SSD": 0.179,
-            "ATSS": 0.455
+            "MobileNetV2-ATSS": 0.455
           },
           "deploy": {
             "YOLOX": 0.534,
             "SSD": 0.179,
-            "ATSS": 0.455
+            "MobileNetV2-ATSS": 0.455
           },
           "nncf": {
             "YOLOX": 0.517,
             "SSD": 0.181,
-            "ATSS": 0.446
+            "MobileNetV2-ATSS": 0.446
           },
           "pot": {
             "YOLOX": 0.531,
             "SSD": 0.18,
-            "ATSS": 0.458
+            "MobileNetV2-ATSS": 0.458
           }
         }
       },
@@ -354,7 +354,7 @@
           "train": {
             "YOLOX": 0.532,
             "SSD": 0.2,
-            "ATSS": 0.443
+            "MobileNetV2-ATSS": 0.443
           }
         }
       },
@@ -363,7 +363,7 @@
           "train": {
             "YOLOX": 0.398,
             "SSD": 0.142,
-            "ATSS": 0.414
+            "MobileNetV2-ATSS": 0.414
           }
         }
       },
@@ -372,27 +372,27 @@
           "train": {
             "YOLOX": 0.545,
             "SSD": 0.19,
-            "ATSS": 0.459
+            "MobileNetV2-ATSS": 0.459
           },
           "export": {
             "YOLOX": 0.549,
             "SSD": 0.19,
-            "ATSS": 0.469
+            "MobileNetV2-ATSS": 0.469
           },
           "deploy": {
             "YOLOX": 0.549,
             "SSD": 0.19,
-            "ATSS": 0.469
+            "MobileNetV2-ATSS": 0.469
           },
           "nncf": {
             "YOLOX": 0.0,
             "SSD": 0.0,
-            "ATSS": 0.0
+            "MobileNetV2-ATSS": 0.0
           },
           "pot": {
             "YOLOX": 0.531,
             "SSD": 0.192,
-            "ATSS": 0.459
+            "MobileNetV2-ATSS": 0.459
           }
         }
       }
@@ -1573,7 +1573,7 @@
           "train": {
             "YOLOX": 4226.84,
             "SSD": 1992.196,
-            "ATSS": 1843.627
+            "MobileNetV2-ATSS": 1843.627
           }
         }
       },
@@ -1582,7 +1582,7 @@
           "train": {
             "YOLOX": 3059.355,
             "SSD": 1439.16,
-            "ATSS": 1531.103
+            "MobileNetV2-ATSS": 1531.103
           }
         }
       },
@@ -1591,7 +1591,7 @@
           "train": {
             "YOLOX": 4962.307,
             "SSD": 6410.017,
-            "ATSS": 6263.435
+            "MobileNetV2-ATSS": 6263.435
           }
         }
       },
@@ -1600,7 +1600,7 @@
           "train": {
             "YOLOX": 1689.117,
             "SSD": 2052.821,
-            "ATSS": 2074.501
+            "MobileNetV2-ATSS": 2074.501
           }
         }
       }
@@ -1973,7 +1973,7 @@
           "train": {
             "YOLOX": 82.169,
             "SSD": 86.989,
-            "ATSS": 73.888
+            "MobileNetV2-ATSS": 73.888
           }
         }
       },
@@ -1982,7 +1982,7 @@
           "train": {
             "YOLOX": 59.154,
             "SSD": 89.412,
-            "ATSS": 62.492
+            "MobileNetV2-ATSS": 62.492
           }
         }
       },
@@ -1991,7 +1991,7 @@
           "train": {
             "YOLOX": 47.199,
             "SSD": 76.703,
-            "ATSS": 50.34
+            "MobileNetV2-ATSS": 50.34
           }
         }
       },
@@ -2000,7 +2000,7 @@
           "train": {
             "YOLOX": 146.561,
             "SSD": 169.937,
-            "ATSS": 84.882
+            "MobileNetV2-ATSS": 84.882
           }
         }
       }
diff --git a/tests/unit/algorithms/detection/test_xai_detection_validity.py b/tests/unit/algorithms/detection/test_xai_detection_validity.py
index 3e903a0b5d6..6d61beed752 100644
--- a/tests/unit/algorithms/detection/test_xai_detection_validity.py
+++ b/tests/unit/algorithms/detection/test_xai_detection_validity.py
@@ -24,19 +24,19 @@
 
 class TestExplainMethods:
     ref_saliency_shapes = {
-        "ATSS": (2, 4, 4),
+        "MobileNetV2-ATSS": (2, 4, 4),
         "SSD": (81, 13, 13),
         "YOLOX": (80, 13, 13),
     }
 
     ref_saliency_vals_det = {
-        "ATSS": np.array([67, 216, 255, 57], dtype=np.uint8),
+        "MobileNetV2-ATSS": np.array([67, 216, 255, 57], dtype=np.uint8),
         "YOLOX": np.array([80, 28, 42, 53, 49, 68, 72, 75, 69, 57, 65, 6, 157], dtype=np.uint8),
         "SSD": np.array([119, 72, 118, 35, 39, 30, 31, 31, 36, 28, 44, 23, 61], dtype=np.uint8),
     }
 
     ref_saliency_vals_det_wo_postprocess = {
-        "ATSS": -0.10465062,
+        "MobileNetV2-ATSS": -0.10465062,
         "YOLOX": 0.04948914,
         "SSD": 0.6629989,
     }
diff --git a/tests/unit/cli/manager/test_config_manager.py b/tests/unit/cli/manager/test_config_manager.py
index 18b4a85ac75..eefb8e6e3a6 100644
--- a/tests/unit/cli/manager/test_config_manager.py
+++ b/tests/unit/cli/manager/test_config_manager.py
@@ -433,7 +433,7 @@ def test__check_rebuild(self, mocker):
         assert not config_manager._check_rebuild()
 
         config_manager.args.model = "SSD"
-        config_manager.template.name = "ATSS"
+        config_manager.template.name = "MobileNetV2-ATSS"
         config_manager.args.train_type = "Semisupervised"
         assert config_manager._check_rebuild()