diff --git a/configs/_base_/datasets/h36m.py b/configs/_base_/datasets/h36m.py
index 68b7e50ad3..914258d5b3 100644
--- a/configs/_base_/datasets/h36m.py
+++ b/configs/_base_/datasets/h36m.py
@@ -148,4 +148,5 @@
         dict(link=('right_elbow', 'right_wrist'), id=15, color=[255, 128, 0])
     },
     joint_weights=[1.] * 17,
-    sigmas=[])
+    sigmas=[],
+    stats_info=dict(bbox_center=(528., 427.), bbox_scale=400.))
diff --git a/mmpose/apis/inference_3d.py b/mmpose/apis/inference_3d.py
index 4b6719dffd..ce60ab5c3d 100644
--- a/mmpose/apis/inference_3d.py
+++ b/mmpose/apis/inference_3d.py
@@ -204,7 +204,7 @@ def _collate_pose_sequence(pose_results, with_track_id=True, target_frame=-1):
 
 def inference_pose_lifter_model(model,
                                 pose_results_2d,
-                                dataset,
+                                dataset=None,
                                 dataset_info=None,
                                 with_track_id=True,
                                 image_size=None,
@@ -245,8 +245,9 @@ def inference_pose_lifter_model(model,
 
     if dataset_info is not None:
         flip_pairs = dataset_info.flip_pairs
-        bbox_center = dataset_info.bbox_center
-        bbox_scale = dataset_info.bbox_scale
+        assert 'stats_info' in dataset_info._dataset_info
+        bbox_center = dataset_info._dataset_info['stats_info']['bbox_center']
+        bbox_scale = dataset_info._dataset_info['stats_info']['bbox_scale']
     else:
         warnings.warn(
             'dataset is deprecated.'
@@ -283,6 +284,7 @@ def inference_pose_lifter_model(model,
         else:
             input_2d_visible = np.ones((T, K, 1), dtype=np.float32)
 
+        # TODO: Will be removed in the later versions
         # Dummy 3D input
         # This is for compatibility with configs in mmpose<=v0.14.0, where a
         # 3D input is required to generate denormalization parameters. This
@@ -348,11 +350,11 @@ def vis_3d_pose_result(model,
                        result,
                        img=None,
                        dataset='Body3DH36MDataset',
+                       dataset_info=None,
                        kpt_score_thr=0.3,
                        radius=8,
                        thickness=2,
                        num_instances=-1,
-                       dataset_info=None,
                        show=False,
                        out_file=None):
     """Visualize the 3D pose estimation results.
diff --git a/mmpose/datasets/dataset_info.py b/mmpose/datasets/dataset_info.py
index 3b9d32a482..ea13bc5a7e 100644
--- a/mmpose/datasets/dataset_info.py
+++ b/mmpose/datasets/dataset_info.py
@@ -4,21 +4,21 @@
 class DatasetInfo:
 
     def __init__(self, dataset_info):
-        self.dataset_info = dataset_info
-        self.dataset_name = self.dataset_info['dataset_name']
-        self.paper_info = self.dataset_info['paper_info']
-        self.keypoint_info = self.dataset_info['keypoint_info']
-        self.skeleton_info = self.dataset_info['skeleton_info']
+        self._dataset_info = dataset_info
+        self.dataset_name = self._dataset_info['dataset_name']
+        self.paper_info = self._dataset_info['paper_info']
+        self.keypoint_info = self._dataset_info['keypoint_info']
+        self.skeleton_info = self._dataset_info['skeleton_info']
         self.joint_weights = np.array(
-            self.dataset_info['joint_weights'], dtype=np.float32)[:, None]
+            self._dataset_info['joint_weights'], dtype=np.float32)[:, None]
 
-        self.sigmas = np.array(self.dataset_info['sigmas'])
+        self.sigmas = np.array(self._dataset_info['sigmas'])
 
         self._parse_keypoint_info()
         self._parse_skeleton_info()
 
     def _parse_skeleton_info(self):
-        """Parse skeleton info.
+        """Parse skeleton information.
 
         - link_num (int): number of links.
         - skeleton (list((2,))): list of links (id).
@@ -42,7 +42,7 @@ def _parse_skeleton_info(self):
         self.pose_link_color = np.array(self.pose_link_color)
 
     def _parse_keypoint_info(self):
-        """Parse keypoint info.
+        """Parse keypoint information.
 
         - keypoint_num (int): number of keypoints.
         - keypoint_id2name (dict): mapping keypoint id to keypoint name.
diff --git a/tests/test_apis/test_inference.py b/tests/test_apis/test_inference.py
index 479d594743..b81d7f3027 100644
--- a/tests/test_apis/test_inference.py
+++ b/tests/test_apis/test_inference.py
@@ -1,9 +1,9 @@
 import numpy as np
-import pytest
 
 from mmpose.apis import (inference_bottom_up_pose_model,
                          inference_top_down_pose_model, init_pose_model,
                          process_mmdet_results, vis_pose_result)
+from mmpose.datasets import DatasetInfo
 
 
 def test_top_down_demo():
@@ -15,14 +15,21 @@ def test_top_down_demo():
         None,
         device='cpu')
     image_name = 'tests/data/coco/000000000785.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
 
     person_result = []
     person_result.append({'bbox': [50, 50, 50, 100]})
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
-        pose_model, image_name, person_result, format='xywh')
+        pose_model,
+        image_name,
+        person_result,
+        format='xywh',
+        dataset_info=dataset_info)
     # show the results
-    vis_pose_result(pose_model, image_name, pose_results)
+    vis_pose_result(
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # AIC demo
     pose_model = init_pose_model(
@@ -31,16 +38,18 @@ def test_top_down_demo():
         None,
         device='cpu')
     image_name = 'tests/data/aic/054d9ce9201beffc76e5ff2169d2af2f027002ca.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
         image_name,
         person_result,
         format='xywh',
-        dataset='TopDownAicDataset')
+        dataset_info=dataset_info)
     # show the results
     vis_pose_result(
-        pose_model, image_name, pose_results, dataset='TopDownAicDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # OneHand10K demo
     # build the pose model from a config file and a checkpoint file
@@ -50,16 +59,18 @@ def test_top_down_demo():
         None,
         device='cpu')
     image_name = 'tests/data/onehand10k/9.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
         image_name,
         person_result,
         format='xywh',
-        dataset='OneHand10KDataset')
+        dataset_info=dataset_info)
     # show the results
     vis_pose_result(
-        pose_model, image_name, pose_results, dataset='OneHand10KDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # InterHand2DDataset demo
     # build the pose model from a config file and a checkpoint file
@@ -69,16 +80,18 @@ def test_top_down_demo():
         None,
         device='cpu')
     image_name = 'tests/data/interhand2.6m/image2017.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
         image_name,
         person_result,
         format='xywh',
-        dataset='InterHand2DDataset')
+        dataset_info=dataset_info)
     # show the results
     vis_pose_result(
-        pose_model, image_name, pose_results, dataset='InterHand2DDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # Face300WDataset demo
     # build the pose model from a config file and a checkpoint file
@@ -88,16 +101,18 @@ def test_top_down_demo():
         None,
         device='cpu')
     image_name = 'tests/data/300w/indoor_020.png'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
         image_name,
         person_result,
         format='xywh',
-        dataset='Face300WDataset')
+        dataset_info=dataset_info)
     # show the results
     vis_pose_result(
-        pose_model, image_name, pose_results, dataset='Face300WDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # FaceAFLWDataset demo
     # build the pose model from a config file and a checkpoint file
@@ -107,16 +122,18 @@ def test_top_down_demo():
         None,
         device='cpu')
     image_name = 'tests/data/aflw/image04476.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
         image_name,
         person_result,
         format='xywh',
-        dataset='FaceAFLWDataset')
+        dataset_info=dataset_info)
     # show the results
     vis_pose_result(
-        pose_model, image_name, pose_results, dataset='FaceAFLWDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # FaceCOFWDataset demo
     # build the pose model from a config file and a checkpoint file
@@ -126,24 +143,18 @@ def test_top_down_demo():
         None,
         device='cpu')
     image_name = 'tests/data/cofw/001766.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
         image_name,
         person_result,
         format='xywh',
-        dataset='FaceCOFWDataset')
+        dataset_info=dataset_info)
     # show the results
     vis_pose_result(
-        pose_model, image_name, pose_results, dataset='FaceCOFWDataset')
-
-    with pytest.raises(NotImplementedError):
-        pose_results, _ = inference_top_down_pose_model(
-            pose_model,
-            image_name,
-            person_result,
-            format='xywh',
-            dataset='test')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
 
 def test_bottom_up_demo():
@@ -156,12 +167,15 @@ def test_bottom_up_demo():
         device='cpu')
 
     image_name = 'tests/data/coco/000000000785.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test'].get(
+        'dataset_info', None))
 
-    pose_results, _ = inference_bottom_up_pose_model(pose_model, image_name)
+    pose_results, _ = inference_bottom_up_pose_model(
+        pose_model, image_name, dataset_info=dataset_info)
 
     # show the results
     vis_pose_result(
-        pose_model, image_name, pose_results, dataset='BottomUpCocoDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
 
 def test_process_mmdet_results():
diff --git a/tests/test_apis/test_inference_3d.py b/tests/test_apis/test_inference_3d.py
index f4ce839675..19b551d463 100644
--- a/tests/test_apis/test_inference_3d.py
+++ b/tests/test_apis/test_inference_3d.py
@@ -11,7 +11,7 @@
                          inference_mesh_model, inference_pose_lifter_model,
                          init_pose_model, vis_3d_mesh_result,
                          vis_3d_pose_result)
-from mmpose.models import build_posenet
+from mmpose.datasets.dataset_info import DatasetInfo
 
 
 def test_pose_lifter_demo():
@@ -31,16 +31,22 @@ def test_pose_lifter_demo():
 
     pose_results_2d = [[pose_det_result]]
 
-    dataset = pose_model.cfg.data['test']['type']
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
 
     pose_results_2d = extract_pose_sequence(
         pose_results_2d, frame_idx=0, causal=False, seq_len=1, step=1)
 
     _ = inference_pose_lifter_model(
-        pose_model, pose_results_2d, dataset, with_track_id=False)
+        pose_model,
+        pose_results_2d,
+        dataset_info=dataset_info,
+        with_track_id=False)
 
     pose_lift_results = inference_pose_lifter_model(
-        pose_model, pose_results_2d, dataset, with_track_id=True)
+        pose_model,
+        pose_results_2d,
+        dataset_info=dataset_info,
+        with_track_id=True)
 
     for res in pose_lift_results:
         res['title'] = 'title'
@@ -48,20 +54,19 @@ def test_pose_lifter_demo():
         pose_model,
         pose_lift_results,
         img=pose_results_2d[0][0]['image_name'],
-        dataset=dataset)
+        dataset_info=dataset_info)
 
     # test special cases
     # Empty 2D results
     _ = inference_pose_lifter_model(
-        pose_model, [[]], dataset, with_track_id=False)
+        pose_model, [[]], dataset_info=dataset_info, with_track_id=False)
 
     if torch.cuda.is_available():
         _ = inference_pose_lifter_model(
-            pose_model.cuda(), pose_results_2d, dataset, with_track_id=False)
-
-    with pytest.raises(NotImplementedError):
-        _ = inference_pose_lifter_model(
-            pose_model, pose_results_2d, dataset='test')
+            pose_model.cuda(),
+            pose_results_2d,
+            dataset_info=dataset_info,
+            with_track_id=False)
 
     # test videopose3d
     pose_model = init_pose_model(
@@ -92,7 +97,7 @@ def test_pose_lifter_demo():
     pose_results_2d = [[pose_det_result_0], [pose_det_result_1],
                        [pose_det_result_2]]
 
-    dataset = pose_model.cfg.data['test']['type']
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
 
     seq_len = pose_model.cfg.test_data_cfg.seq_len
     pose_results_2d_seq = extract_pose_sequence(
@@ -101,7 +106,7 @@ def test_pose_lifter_demo():
     pose_lift_results = inference_pose_lifter_model(
         pose_model,
         pose_results_2d_seq,
-        dataset,
+        dataset_info=dataset_info,
         with_track_id=True,
         image_size=[1000, 1000],
         norm_pose_2d=True)
@@ -112,7 +117,8 @@ def test_pose_lifter_demo():
         pose_model,
         pose_lift_results,
         img=pose_results_2d[0][0]['image_name'],
-        dataset=dataset)
+        dataset_info=dataset_info,
+    )
 
 
 def test_interhand3d_demo():
@@ -132,6 +138,7 @@ def test_interhand3d_demo():
     }
     det_results = [det_result]
     dataset = pose_model.cfg.data['test']['type']
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
 
     pose_results = inference_interhand_3d_model(
         pose_model, image_name, det_results, dataset=dataset)
@@ -143,7 +150,7 @@ def test_interhand3d_demo():
         pose_model,
         result=pose_results,
         img=det_results[0]['image_name'],
-        dataset=dataset,
+        dataset_info=dataset_info,
     )
 
     # test special cases
@@ -162,7 +169,6 @@ def test_interhand3d_demo():
 
 def test_body_mesh_demo():
     # H36M demo
-    device = 'cpu'
     config = 'configs/body/3d_mesh_sview_rgb_img/hmr' \
              '/mixed/res50_mixed_224x224.py'
     config = mmcv.Config.fromfile(config)
@@ -176,12 +182,9 @@ def test_body_mesh_demo():
             tmpdir, 'test_joint_regressor.npy')
         # generate weight file for SMPL model.
         generate_smpl_weight_file(tmpdir)
-        pose_model = build_posenet(config.model)
+        pose_model = init_pose_model(config, device='cpu')
 
     assert pose_model is not None, 'Fail to build pose model'
-    pose_model.cfg = config
-    pose_model.to(device)
-    pose_model.eval()
 
     image_name = 'tests/data/h36m/S1_Directions_1.54138969_000001.jpg'
     det_result = {
diff --git a/tests/test_apis/test_inference_tracking.py b/tests/test_apis/test_inference_tracking.py
index ae2a321219..8a847c5d74 100644
--- a/tests/test_apis/test_inference_tracking.py
+++ b/tests/test_apis/test_inference_tracking.py
@@ -1,8 +1,7 @@
-import pytest
-
 from mmpose.apis import (get_track_id, inference_bottom_up_pose_model,
                          inference_top_down_pose_model, init_pose_model,
                          vis_pose_tracking_result)
+from mmpose.datasets.dataset_info import DatasetInfo
 
 
 def test_top_down_pose_tracking_demo():
@@ -14,15 +13,20 @@ def test_top_down_pose_tracking_demo():
         None,
         device='cpu')
     image_name = 'tests/data/coco/000000000785.jpg'
-
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
     person_result = [{'bbox': [50, 50, 50, 100]}]
 
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
-        pose_model, image_name, person_result, format='xywh')
+        pose_model,
+        image_name,
+        person_result,
+        format='xywh',
+        dataset_info=dataset_info)
     pose_results, next_id = get_track_id(pose_results, [], next_id=0)
     # show the results
-    vis_pose_tracking_result(pose_model, image_name, pose_results)
+    vis_pose_tracking_result(
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
     pose_results_last = pose_results
 
     # AIC demo
@@ -32,13 +36,14 @@ def test_top_down_pose_tracking_demo():
         None,
         device='cpu')
     image_name = 'tests/data/aic/054d9ce9201beffc76e5ff2169d2af2f027002ca.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
         image_name,
         person_result,
         format='xywh',
-        dataset='TopDownAicDataset')
+        dataset_info=dataset_info)
     pose_results, next_id = get_track_id(pose_results, pose_results_last,
                                          next_id)
     for pose_result in pose_results:
@@ -48,7 +53,7 @@ def test_top_down_pose_tracking_demo():
 
     # show the results
     vis_pose_tracking_result(
-        pose_model, image_name, pose_results, dataset='TopDownAicDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # OneHand10K demo
     # build the pose model from a config file and a checkpoint file
@@ -58,6 +63,7 @@ def test_top_down_pose_tracking_demo():
         None,
         device='cpu')
     image_name = 'tests/data/onehand10k/9.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
@@ -65,12 +71,12 @@ def test_top_down_pose_tracking_demo():
             'bbox': [10, 10, 30, 30]
         }],
         format='xywh',
-        dataset='OneHand10KDataset')
+        dataset_info=dataset_info)
     pose_results, next_id = get_track_id(pose_results, pose_results_last,
                                          next_id)
     # show the results
     vis_pose_tracking_result(
-        pose_model, image_name, pose_results, dataset='OneHand10KDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     # InterHand2D demo
     pose_model = init_pose_model(
@@ -79,6 +85,7 @@ def test_top_down_pose_tracking_demo():
         None,
         device='cpu')
     image_name = 'tests/data/interhand2.6m/image2017.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
@@ -86,11 +93,11 @@ def test_top_down_pose_tracking_demo():
             'bbox': [50, 50, 0, 0]
         }],
         format='xywh',
-        dataset='InterHand2DDataset')
+        dataset_info=dataset_info)
     pose_results, next_id = get_track_id(pose_results, [], next_id=0)
     # show the results
     vis_pose_tracking_result(
-        pose_model, image_name, pose_results, dataset='InterHand2DDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
     pose_results_last = pose_results
 
     # MPII demo
@@ -100,6 +107,7 @@ def test_top_down_pose_tracking_demo():
         None,
         device='cpu')
     image_name = 'tests/data/mpii/004645041.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
     # test a single image, with a list of bboxes.
     pose_results, _ = inference_top_down_pose_model(
         pose_model,
@@ -107,16 +115,12 @@ def test_top_down_pose_tracking_demo():
             'bbox': [50, 50, 0, 0]
         }],
         format='xywh',
-        dataset='TopDownMpiiDataset')
+        dataset_info=dataset_info)
     pose_results, next_id = get_track_id(pose_results, pose_results_last,
                                          next_id)
     # show the results
     vis_pose_tracking_result(
-        pose_model, image_name, pose_results, dataset='TopDownMpiiDataset')
-
-    with pytest.raises(NotImplementedError):
-        vis_pose_tracking_result(
-            pose_model, image_name, pose_results, dataset='test')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
 
 def test_bottom_up_pose_tracking_demo():
@@ -129,14 +133,16 @@ def test_bottom_up_pose_tracking_demo():
         device='cpu')
 
     image_name = 'tests/data/coco/000000000785.jpg'
+    dataset_info = DatasetInfo(pose_model.cfg.data['test']['dataset_info'])
 
-    pose_results, _ = inference_bottom_up_pose_model(pose_model, image_name)
+    pose_results, _ = inference_bottom_up_pose_model(
+        pose_model, image_name, dataset_info=dataset_info)
 
     pose_results, next_id = get_track_id(pose_results, [], next_id=0)
 
     # show the results
     vis_pose_tracking_result(
-        pose_model, image_name, pose_results, dataset='BottomUpCocoDataset')
+        pose_model, image_name, pose_results, dataset_info=dataset_info)
 
     pose_results_last = pose_results
 
diff --git a/tests/test_backward_compatibility/test_dataset_compatibility.py b/tests/test_backward_compatibility/test_dataset_compatibility.py
deleted file mode 100644
index 94c6a4f479..0000000000
--- a/tests/test_backward_compatibility/test_dataset_compatibility.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import pytest
-
-from mmpose.datasets.datasets.animal.animal_base_dataset import \
-    AnimalBaseDataset
-from mmpose.datasets.datasets.bottom_up.bottom_up_base_dataset import \
-    BottomUpBaseDataset
-from mmpose.datasets.datasets.face.face_base_dataset import FaceBaseDataset
-from mmpose.datasets.datasets.fashion.fashion_fase_dataset import \
-    FashionBaseDataset
-from mmpose.datasets.datasets.hand.hand_base_dataset import HandBaseDataset
-from mmpose.datasets.datasets.top_down.topdown_base_dataset import \
-    TopDownBaseDataset
-
-
-@pytest.mark.parametrize('BaseDataset',
-                         (AnimalBaseDataset, BottomUpBaseDataset,
-                          FaceBaseDataset, FashionBaseDataset, HandBaseDataset,
-                          TopDownBaseDataset))
-def test_dataset_base_class(BaseDataset):
-    with pytest.raises(ImportError):
-
-        class Dataset(BaseDataset):
-            pass
-
-        _ = Dataset()
diff --git a/tests/test_backward_compatibility/test_dataset_info_compatibility.py b/tests/test_backward_compatibility/test_dataset_info_compatibility.py
new file mode 100644
index 0000000000..e1b8c5ebaf
--- /dev/null
+++ b/tests/test_backward_compatibility/test_dataset_info_compatibility.py
@@ -0,0 +1,162 @@
+import numpy as np
+import pytest
+
+from mmpose.apis import (extract_pose_sequence, get_track_id,
+                         inference_bottom_up_pose_model,
+                         inference_pose_lifter_model,
+                         inference_top_down_pose_model, init_pose_model,
+                         vis_3d_pose_result, vis_pose_result,
+                         vis_pose_tracking_result)
+from mmpose.datasets.datasets.animal.animal_base_dataset import \
+    AnimalBaseDataset
+from mmpose.datasets.datasets.bottom_up.bottom_up_base_dataset import \
+    BottomUpBaseDataset
+from mmpose.datasets.datasets.face.face_base_dataset import FaceBaseDataset
+from mmpose.datasets.datasets.fashion.fashion_fase_dataset import \
+    FashionBaseDataset
+from mmpose.datasets.datasets.hand.hand_base_dataset import HandBaseDataset
+from mmpose.datasets.datasets.top_down.topdown_base_dataset import \
+    TopDownBaseDataset
+
+
+@pytest.mark.parametrize('BaseDataset',
+                         (AnimalBaseDataset, BottomUpBaseDataset,
+                          FaceBaseDataset, FashionBaseDataset, HandBaseDataset,
+                          TopDownBaseDataset))
+def test_dataset_base_class(BaseDataset):
+    with pytest.raises(ImportError):
+
+        class Dataset(BaseDataset):
+            pass
+
+        _ = Dataset()
+
+
+def test_inference_without_dataset_info():
+    # Top down
+    pose_model = init_pose_model(
+        'configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/'
+        'coco/res50_coco_256x192.py',
+        None,
+        device='cpu')
+    image_name = 'tests/data/coco/000000000785.jpg'
+
+    person_result = []
+    person_result.append({'bbox': [50, 50, 50, 100]})
+
+    with pytest.warns(DeprecationWarning):
+        pose_results, _ = inference_top_down_pose_model(
+            pose_model, image_name, person_result, format='xywh')
+
+    with pytest.warns(DeprecationWarning):
+        vis_pose_result(pose_model, image_name, pose_results)
+
+    with pytest.raises(NotImplementedError):
+        with pytest.warns(DeprecationWarning):
+            pose_results, _ = inference_top_down_pose_model(
+                pose_model,
+                image_name,
+                person_result,
+                format='xywh',
+                dataset='test')
+
+    # Bottom up
+    pose_model = init_pose_model(
+        'configs/body/2d_kpt_sview_rgb_img/associative_embedding/'
+        'coco/res50_coco_512x512.py',
+        None,
+        device='cpu')
+
+    image_name = 'tests/data/coco/000000000785.jpg'
+    with pytest.warns(DeprecationWarning):
+        pose_results, _ = inference_bottom_up_pose_model(
+            pose_model, image_name)
+    with pytest.warns(DeprecationWarning):
+        vis_pose_result(pose_model, image_name, pose_results)
+
+    # Top down tracking
+    pose_model = init_pose_model(
+        'configs/body/2d_kpt_sview_rgb_img/topdown_heatmap/'
+        'coco/res50_coco_256x192.py',
+        None,
+        device='cpu')
+    image_name = 'tests/data/coco/000000000785.jpg'
+    person_result = [{'bbox': [50, 50, 50, 100]}]
+
+    with pytest.warns(DeprecationWarning):
+        pose_results, _ = inference_top_down_pose_model(
+            pose_model, image_name, person_result, format='xywh')
+
+    pose_results, _ = get_track_id(pose_results, [], next_id=0)
+
+    with pytest.warns(DeprecationWarning):
+        vis_pose_tracking_result(pose_model, image_name, pose_results)
+
+    with pytest.raises(NotImplementedError):
+        with pytest.warns(DeprecationWarning):
+            vis_pose_tracking_result(
+                pose_model, image_name, pose_results, dataset='test')
+
+    # Bottom up tracking
+    pose_model = init_pose_model(
+        'configs/body/2d_kpt_sview_rgb_img/associative_embedding/'
+        'coco/res50_coco_512x512.py',
+        None,
+        device='cpu')
+
+    image_name = 'tests/data/coco/000000000785.jpg'
+    with pytest.warns(DeprecationWarning):
+        pose_results, _ = inference_bottom_up_pose_model(
+            pose_model, image_name)
+
+    pose_results, next_id = get_track_id(pose_results, [], next_id=0)
+
+    with pytest.warns(DeprecationWarning):
+        vis_pose_tracking_result(
+            pose_model,
+            image_name,
+            pose_results,
+            dataset='BottomUpCocoDataset')
+
+    # Pose lifting
+    pose_model = init_pose_model(
+        'configs/body/3d_kpt_sview_rgb_img/pose_lift/'
+        'h36m/simplebaseline3d_h36m.py',
+        None,
+        device='cpu')
+
+    pose_det_result = {
+        'keypoints': np.zeros((17, 3)),
+        'bbox': [50, 50, 50, 50],
+        'track_id': 0,
+        'image_name': 'tests/data/h36m/S1_Directions_1.54138969_000001.jpg',
+    }
+
+    pose_results_2d = [[pose_det_result]]
+
+    dataset = pose_model.cfg.data['test']['type']
+
+    pose_results_2d = extract_pose_sequence(
+        pose_results_2d, frame_idx=0, causal=False, seq_len=1, step=1)
+
+    with pytest.warns(DeprecationWarning):
+        _ = inference_pose_lifter_model(
+            pose_model, pose_results_2d, dataset, with_track_id=False)
+
+    with pytest.warns(DeprecationWarning):
+        pose_lift_results = inference_pose_lifter_model(
+            pose_model, pose_results_2d, dataset, with_track_id=True)
+
+    for res in pose_lift_results:
+        res['title'] = 'title'
+    with pytest.warns(DeprecationWarning):
+        vis_3d_pose_result(
+            pose_model,
+            pose_lift_results,
+            img=pose_results_2d[0][0]['image_name'],
+            dataset=dataset)
+
+    with pytest.raises(NotImplementedError):
+        with pytest.warns(DeprecationWarning):
+            _ = inference_pose_lifter_model(
+                pose_model, pose_results_2d, dataset='test')
diff --git a/tests/test_datasets/test_animal_dataset.py b/tests/test_datasets/test_animal_dataset.py
index 0c92e0f910..31057f7f03 100644
--- a/tests/test_datasets/test_animal_dataset.py
+++ b/tests/test_datasets/test_animal_dataset.py
@@ -3,6 +3,7 @@
 
 import numpy as np
 import pytest
+from mmcv import Config
 from numpy.testing import assert_almost_equal
 
 from mmpose.datasets import DATASETS
@@ -60,6 +61,8 @@ def convert_db_to_output(db, batch_size=2, keys=None, is_3d=False):
 def test_animal_horse10_dataset():
     dataset = 'AnimalHorse10Dataset'
     dataset_class = DATASETS.get(dataset)
+    dataset_info = Config.fromfile(
+        'configs/_base_/datasets/horse10.py').dataset_info
 
     channel_cfg = dict(
         num_output_channels=22,
@@ -88,6 +91,7 @@ def test_animal_horse10_dataset():
         ann_file='tests/data/horse10/test_horse10.json',
         img_prefix='tests/data/horse10/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=True)
 
@@ -95,6 +99,7 @@ def test_animal_horse10_dataset():
         ann_file='tests/data/horse10/test_horse10.json',
         img_prefix='tests/data/horse10/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=False)
 
@@ -115,6 +120,8 @@ def test_animal_horse10_dataset():
 def test_animal_fly_dataset():
     dataset = 'AnimalFlyDataset'
     dataset_class = DATASETS.get(dataset)
+    dataset_info = Config.fromfile(
+        'configs/_base_/datasets/fly.py').dataset_info
 
     channel_cfg = dict(
         num_output_channels=32,
@@ -144,6 +151,7 @@ def test_animal_fly_dataset():
         ann_file='tests/data/fly/test_fly.json',
         img_prefix='tests/data/fly/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=True)
 
@@ -151,6 +159,7 @@ def test_animal_fly_dataset():
         ann_file='tests/data/fly/test_fly.json',
         img_prefix='tests/data/fly/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=False)
 
@@ -171,6 +180,8 @@ def test_animal_fly_dataset():
 def test_animal_locust_dataset():
     dataset = 'AnimalLocustDataset'
     dataset_class = DATASETS.get(dataset)
+    dataset_info = Config.fromfile(
+        'configs/_base_/datasets/locust.py').dataset_info
 
     channel_cfg = dict(
         num_output_channels=35,
@@ -201,6 +212,7 @@ def test_animal_locust_dataset():
         ann_file='tests/data/locust/test_locust.json',
         img_prefix='tests/data/locust/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=True)
 
@@ -208,6 +220,7 @@ def test_animal_locust_dataset():
         ann_file='tests/data/locust/test_locust.json',
         img_prefix='tests/data/locust/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=False)
 
@@ -228,6 +241,8 @@ def test_animal_locust_dataset():
 def test_animal_zebra_dataset():
     dataset = 'AnimalZebraDataset'
     dataset_class = DATASETS.get(dataset)
+    dataset_info = Config.fromfile(
+        'configs/_base_/datasets/zebra.py').dataset_info
 
     channel_cfg = dict(
         num_output_channels=9,
@@ -251,6 +266,7 @@ def test_animal_zebra_dataset():
         ann_file='tests/data/zebra/test_zebra.json',
         img_prefix='tests/data/zebra/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=True)
 
@@ -258,6 +274,7 @@ def test_animal_zebra_dataset():
         ann_file='tests/data/zebra/test_zebra.json',
         img_prefix='tests/data/zebra/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=False)
 
@@ -278,6 +295,8 @@ def test_animal_zebra_dataset():
 def test_animal_ATRW_dataset():
     dataset = 'AnimalATRWDataset'
     dataset_class = DATASETS.get(dataset)
+    dataset_info = Config.fromfile(
+        'configs/_base_/datasets/atrw.py').dataset_info
 
     channel_cfg = dict(
         num_output_channels=15,
@@ -309,6 +328,7 @@ def test_animal_ATRW_dataset():
         ann_file='tests/data/atrw/test_atrw.json',
         img_prefix='tests/data/atrw/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=True)
 
@@ -316,6 +336,7 @@ def test_animal_ATRW_dataset():
         ann_file='tests/data/atrw/test_atrw.json',
         img_prefix='tests/data/atrw/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=False)
 
@@ -336,6 +357,8 @@ def test_animal_ATRW_dataset():
 def test_animal_Macaque_dataset():
     dataset = 'AnimalMacaqueDataset'
     dataset_class = DATASETS.get(dataset)
+    dataset_info = Config.fromfile(
+        'configs/_base_/datasets/macaque.py').dataset_info
 
     channel_cfg = dict(
         num_output_channels=17,
@@ -369,6 +392,7 @@ def test_animal_Macaque_dataset():
         ann_file='tests/data/macaque/test_macaque.json',
         img_prefix='tests/data/macaque/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=True)
 
@@ -376,6 +400,7 @@ def test_animal_Macaque_dataset():
         ann_file='tests/data/macaque/test_macaque.json',
         img_prefix='tests/data/macaque/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=False)
 
@@ -396,6 +421,8 @@ def test_animal_Macaque_dataset():
 def test_animalpose_dataset():
     dataset = 'AnimalPoseDataset'
     dataset_class = DATASETS.get(dataset)
+    dataset_info = Config.fromfile(
+        'configs/_base_/datasets/animalpose.py').dataset_info
 
     channel_cfg = dict(
         num_output_channels=20,
@@ -433,6 +460,7 @@ def test_animalpose_dataset():
         ann_file='tests/data/animalpose/test_animalpose.json',
         img_prefix='tests/data/animalpose/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=True)
 
@@ -440,6 +468,7 @@ def test_animalpose_dataset():
         ann_file='tests/data/animalpose/test_animalpose.json',
         img_prefix='tests/data/animalpose/',
         data_cfg=data_cfg_copy,
+        dataset_info=dataset_info,
         pipeline=[],
         test_mode=False)