diff --git a/src/otx/recipe/detection/atss_resnext101_tile.yaml b/src/otx/recipe/detection/atss_resnext101_tile.yaml
new file mode 100644
index 00000000000..0815453c46b
--- /dev/null
+++ b/src/otx/recipe/detection/atss_resnext101_tile.yaml
@@ -0,0 +1,55 @@
+model:
+  class_path: otx.algo.detection.atss.ResNeXt101ATSS
+  init_args:
+    label_info: 80
+
+    optimizer:
+      class_path: torch.optim.SGD
+      init_args:
+        lr: 0.004
+        momentum: 0.9
+        weight_decay: 0.0001
+
+    scheduler:
+      class_path: otx.core.schedulers.LinearWarmupSchedulerCallable
+      init_args:
+        num_warmup_steps: 3
+        main_scheduler_callable:
+          class_path: lightning.pytorch.cli.ReduceLROnPlateau
+          init_args:
+            mode: max
+            factor: 0.1
+            patience: 4
+            monitor: val/map_50
+
+engine:
+  task: DETECTION
+  device: auto
+
+callback_monitor: val/map_50
+
+data: ../_base_/data/detection.yaml
+overrides:
+  gradient_clip_val: 35.0
+  callbacks:
+    - class_path: otx.algo.callbacks.adaptive_train_scheduling.AdaptiveTrainScheduling
+      init_args:
+        max_interval: 5
+        decay: -0.025
+        min_lrschedule_patience: 3
+
+  data:
+    tile_config:
+      enable_tiler: true
+      enable_adaptive_tiling: true
+
+    train_subset:
+      batch_size: 4
+      sampler:
+        class_path: otx.algo.samplers.balanced_sampler.BalancedSampler
+
+    val_subset:
+      batch_size: 4
+
+    test_subset:
+      batch_size: 4
diff --git a/src/otx/recipe/detection/rtdetr_101_tile.yaml b/src/otx/recipe/detection/rtdetr_101_tile.yaml
new file mode 100644
index 00000000000..affbd103fbe
--- /dev/null
+++ b/src/otx/recipe/detection/rtdetr_101_tile.yaml
@@ -0,0 +1,114 @@
+model:
+  class_path: otx.algo.detection.rtdetr.RTDETR101
+  init_args:
+    label_info: 80
+
+    optimizer:
+      class_path: torch.optim.AdamW
+      init_args:
+        lr: 0.0001
+        betas: [0.9, 0.999]
+        weight_decay: 0.0001
+
+    scheduler:
+      class_path: otx.core.schedulers.LinearWarmupSchedulerCallable
+      init_args:
+        num_warmup_steps: 5
+        main_scheduler_callable:
+          class_path: lightning.pytorch.cli.ReduceLROnPlateau
+          init_args:
+            mode: max
+            factor: 0.1
+            patience: 6
+            monitor: val/map_50
+
+engine:
+  task: DETECTION
+  device: auto
+
+callback_monitor: val/map_50
+
+data: ../_base_/data/torchvision_base.yaml
+overrides:
+  callbacks:
+    - class_path: otx.algo.callbacks.adaptive_train_scheduling.AdaptiveTrainScheduling
+      init_args:
+        max_interval: 1
+        decay: -0.025
+        min_lrschedule_patience: 3
+    - class_path: otx.algo.callbacks.adaptive_early_stopping.EarlyStoppingWithWarmup
+      init_args:
+        monitor: null
+        mode: max
+        patience: 10
+        check_on_train_epoch_end: false
+        min_delta: 0.001
+        warmup_iters: 100
+        warmup_epochs: 7
+
+  data:
+    tile_config:
+      enable_tiler: true
+      enable_adaptive_tiling: true
+    input_size:
+      - 640
+      - 640
+    task: DETECTION
+    stack_images: true
+    data_format: coco_instances
+    train_subset:
+      batch_size: 4
+      to_tv_image: true
+      transforms:
+        - class_path: torchvision.transforms.v2.RandomPhotometricDistort
+          init_args:
+            p: 0.5
+        - class_path: torchvision.transforms.v2.RandomZoomOut
+          init_args:
+            fill: 0
+        - class_path: otx.core.data.transform_libs.torchvision.RandomFlip
+          init_args:
+            prob: 0.5
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
+        - class_path: torchvision.transforms.v2.SanitizeBoundingBoxes
+      sampler:
+        class_path: otx.algo.samplers.balanced_sampler.BalancedSampler
+
+    val_subset:
+      batch_size: 8
+      to_tv_image: true
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
+
+    test_subset:
+      batch_size: 8
+      to_tv_image: true
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
diff --git a/src/otx/recipe/detection/rtdetr_18_tile.yaml b/src/otx/recipe/detection/rtdetr_18_tile.yaml
new file mode 100644
index 00000000000..71c2b3a715c
--- /dev/null
+++ b/src/otx/recipe/detection/rtdetr_18_tile.yaml
@@ -0,0 +1,113 @@
+model:
+  class_path: otx.algo.detection.rtdetr.RTDETR18
+  init_args:
+    label_info: 80
+
+    optimizer:
+      class_path: torch.optim.AdamW
+      init_args:
+        lr: 0.0001
+        betas: [0.9, 0.999]
+        weight_decay: 0.0001
+
+    scheduler:
+      class_path: otx.core.schedulers.LinearWarmupSchedulerCallable
+      init_args:
+        num_warmup_steps: 5
+        main_scheduler_callable:
+          class_path: lightning.pytorch.cli.ReduceLROnPlateau
+          init_args:
+            mode: max
+            factor: 0.1
+            patience: 6
+            monitor: val/map_50
+engine:
+  task: DETECTION
+  device: auto
+
+callback_monitor: val/map_50
+
+data: ../_base_/data/torchvision_base.yaml
+overrides:
+  callbacks:
+    - class_path: otx.algo.callbacks.adaptive_train_scheduling.AdaptiveTrainScheduling
+      init_args:
+        max_interval: 1
+        decay: -0.025
+        min_lrschedule_patience: 3
+    - class_path: otx.algo.callbacks.adaptive_early_stopping.EarlyStoppingWithWarmup
+      init_args:
+        monitor: null
+        mode: max
+        patience: 10
+        check_on_train_epoch_end: false
+        min_delta: 0.001
+        warmup_iters: 100
+        warmup_epochs: 7
+
+  data:
+    tile_config:
+      enable_tiler: true
+      enable_adaptive_tiling: true
+    input_size:
+      - 640
+      - 640
+    task: DETECTION
+    stack_images: true
+    data_format: coco_instances
+    train_subset:
+      batch_size: 4
+      to_tv_image: true
+      transforms:
+        - class_path: torchvision.transforms.v2.RandomPhotometricDistort
+          init_args:
+            p: 0.5
+        - class_path: torchvision.transforms.v2.RandomZoomOut
+          init_args:
+            fill: 0
+        - class_path: otx.core.data.transform_libs.torchvision.RandomFlip
+          init_args:
+            prob: 0.5
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
+        - class_path: torchvision.transforms.v2.SanitizeBoundingBoxes
+      sampler:
+        class_path: otx.algo.samplers.balanced_sampler.BalancedSampler
+
+    val_subset:
+      batch_size: 8
+      to_tv_image: true
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
+
+    test_subset:
+      batch_size: 8
+      to_tv_image: true
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
diff --git a/src/otx/recipe/detection/rtdetr_50_tile.yaml b/src/otx/recipe/detection/rtdetr_50_tile.yaml
new file mode 100644
index 00000000000..b9a96155a54
--- /dev/null
+++ b/src/otx/recipe/detection/rtdetr_50_tile.yaml
@@ -0,0 +1,114 @@
+model:
+  class_path: otx.algo.detection.rtdetr.RTDETR50
+  init_args:
+    label_info: 80
+
+    optimizer:
+      class_path: torch.optim.AdamW
+      init_args:
+        lr: 0.0001
+        betas: [0.9, 0.999]
+        weight_decay: 0.0001
+
+    scheduler:
+      class_path: otx.core.schedulers.LinearWarmupSchedulerCallable
+      init_args:
+        num_warmup_steps: 5
+        main_scheduler_callable:
+          class_path: lightning.pytorch.cli.ReduceLROnPlateau
+          init_args:
+            mode: max
+            factor: 0.1
+            patience: 6
+            monitor: val/map_50
+
+engine:
+  task: DETECTION
+  device: auto
+
+callback_monitor: val/map_50
+
+data: ../_base_/data/torchvision_base.yaml
+overrides:
+  callbacks:
+    - class_path: otx.algo.callbacks.adaptive_train_scheduling.AdaptiveTrainScheduling
+      init_args:
+        max_interval: 1
+        decay: -0.025
+        min_lrschedule_patience: 3
+    - class_path: otx.algo.callbacks.adaptive_early_stopping.EarlyStoppingWithWarmup
+      init_args:
+        monitor: null
+        mode: max
+        patience: 10
+        check_on_train_epoch_end: false
+        min_delta: 0.001
+        warmup_iters: 100
+        warmup_epochs: 7
+
+  data:
+    tile_config:
+      enable_tiler: true
+      enable_adaptive_tiling: true
+    input_size:
+      - 640
+      - 640
+    task: DETECTION
+    stack_images: true
+    data_format: coco_instances
+    train_subset:
+      batch_size: 4
+      to_tv_image: true
+      transforms:
+        - class_path: torchvision.transforms.v2.RandomPhotometricDistort
+          init_args:
+            p: 0.5
+        - class_path: torchvision.transforms.v2.RandomZoomOut
+          init_args:
+            fill: 0
+        - class_path: otx.core.data.transform_libs.torchvision.RandomFlip
+          init_args:
+            prob: 0.5
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
+        - class_path: torchvision.transforms.v2.SanitizeBoundingBoxes
+      sampler:
+        class_path: otx.algo.samplers.balanced_sampler.BalancedSampler
+
+    val_subset:
+      batch_size: 8
+      to_tv_image: true
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
+
+    test_subset:
+      batch_size: 8
+      to_tv_image: true
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: false
+            transform_bbox: true
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+            scale: true
diff --git a/src/otx/recipe/detection/rtmdet_tiny_tile.yaml b/src/otx/recipe/detection/rtmdet_tiny_tile.yaml
new file mode 100644
index 00000000000..5417b86c683
--- /dev/null
+++ b/src/otx/recipe/detection/rtmdet_tiny_tile.yaml
@@ -0,0 +1,129 @@
+model:
+  class_path: otx.algo.detection.rtmdet.RTMDetTiny
+  init_args:
+    label_info: 80
+
+    optimizer:
+      class_path: torch.optim.AdamW
+      init_args:
+        lr: 0.0007
+        weight_decay: 0.05
+
+    scheduler:
+      class_path: otx.core.schedulers.LinearWarmupSchedulerCallable
+      init_args:
+        num_warmup_steps: 3
+        main_scheduler_callable:
+          class_path: lightning.pytorch.cli.ReduceLROnPlateau
+          init_args:
+            mode: max
+            factor: 0.1
+            patience: 4
+            monitor: val/map_50
+
+engine:
+  task: DETECTION
+  device: auto
+
+callback_monitor: val/map_50
+
+data: ../_base_/data/detection.yaml
+overrides:
+  reset:
+    - data.train_subset.transforms
+    - data.val_subset.transforms
+    - data.test_subset.transforms
+
+  gradient_clip_val: 35.0
+  data:
+    tile_config:
+      enable_tiler: true
+      enable_adaptive_tiling: true
+    input_size:
+      - 640
+      - 640
+    image_color_channel: BGR
+    train_subset:
+      batch_size: 8
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.CachedMosaic
+          init_args:
+            img_scale: $(input_size)
+            max_cached_images: 20
+            random_pop: false
+        - class_path: otx.core.data.transform_libs.torchvision.RandomResize
+          init_args:
+            scale: $(input_size) * 2
+            ratio_range:
+              - 0.5
+              - 2.0
+            keep_ratio: true
+            transform_bbox: true
+        - class_path: otx.core.data.transform_libs.torchvision.RandomCrop
+          init_args:
+            crop_size: $(input_size)
+        - class_path: otx.core.data.transform_libs.torchvision.YOLOXHSVRandomAug
+        - class_path: otx.core.data.transform_libs.torchvision.RandomFlip
+          init_args:
+            prob: 0.5
+        - class_path: otx.core.data.transform_libs.torchvision.Pad
+          init_args:
+            size: $(input_size)
+            pad_val: 114
+        - class_path: otx.core.data.transform_libs.torchvision.CachedMixUp
+          init_args:
+            img_scale: $(input_size)
+            ratio_range:
+              - 1.0
+              - 1.0
+            max_cached_images: 10
+            random_pop: false
+            prob: 0.5
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+        - class_path: torchvision.transforms.v2.Normalize
+          init_args:
+            mean: [103.53, 116.28, 123.675]
+            std: [57.375, 57.12, 58.395]
+
+    val_subset:
+      batch_size: 8
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: true
+        - class_path: otx.core.data.transform_libs.torchvision.Pad
+          init_args:
+            size: $(input_size)
+            pad_val: 114
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+        - class_path: torchvision.transforms.v2.Normalize
+          init_args:
+            mean: [103.53, 116.28, 123.675]
+            std: [57.375, 57.12, 58.395]
+
+    test_subset:
+      batch_size: 8
+      transforms:
+        - class_path: otx.core.data.transform_libs.torchvision.Resize
+          init_args:
+            scale: $(input_size)
+            keep_ratio: true
+        - class_path: otx.core.data.transform_libs.torchvision.Pad
+          init_args:
+            size: $(input_size)
+            pad_val: 114
+            is_numpy_to_tvtensor: true
+        - class_path: torchvision.transforms.v2.ToDtype
+          init_args:
+            dtype: ${as_torch_dtype:torch.float32}
+        - class_path: torchvision.transforms.v2.Normalize
+          init_args:
+            mean: [103.53, 116.28, 123.675]
+            std: [57.375, 57.12, 58.395]