diff --git a/mmaction/datasets/pipelines/loading.py b/mmaction/datasets/pipelines/loading.py
index 79a6656c9c..7365eb7054 100644
--- a/mmaction/datasets/pipelines/loading.py
+++ b/mmaction/datasets/pipelines/loading.py
@@ -99,6 +99,8 @@ class SampleFrames:
         start_index (None): This argument is deprecated and moved to dataset
             class (``BaseDataset``, ``VideoDatset``, ``RawframeDataset``, etc),
             see this: https://github.com/open-mmlab/mmaction2/pull/89.
+        keep_tail_frames (bool): Whether to keep tail frames when sampling.
+            Default: False.
     """
 
     def __init__(self,
@@ -109,7 +111,8 @@ def __init__(self,
                  twice_sample=False,
                  out_of_bound_opt='loop',
                  test_mode=False,
-                 start_index=None):
+                 start_index=None,
+                 keep_tail_frames=False):
 
         self.clip_len = clip_len
         self.frame_interval = frame_interval
@@ -118,6 +121,7 @@ def __init__(self,
         self.twice_sample = twice_sample
         self.out_of_bound_opt = out_of_bound_opt
         self.test_mode = test_mode
+        self.keep_tail_frames = keep_tail_frames
         assert self.out_of_bound_opt in ['loop', 'repeat_last']
 
         if start_index is not None:
@@ -140,21 +144,32 @@ def _get_train_clips(self, num_frames):
             np.ndarray: Sampled frame indices in train mode.
         """
         ori_clip_len = self.clip_len * self.frame_interval
-        avg_interval = (num_frames - ori_clip_len + 1) // self.num_clips
 
-        if avg_interval > 0:
-            base_offsets = np.arange(self.num_clips) * avg_interval
-            clip_offsets = base_offsets + np.random.randint(
-                avg_interval, size=self.num_clips)
-        elif num_frames > max(self.num_clips, ori_clip_len):
-            clip_offsets = np.sort(
-                np.random.randint(
-                    num_frames - ori_clip_len + 1, size=self.num_clips))
-        elif avg_interval == 0:
-            ratio = (num_frames - ori_clip_len + 1.0) / self.num_clips
-            clip_offsets = np.around(np.arange(self.num_clips) * ratio)
+        if self.keep_tail_frames:
+            avg_interval = (num_frames - ori_clip_len + 1) / float(
+                self.num_clips)
+            if num_frames > ori_clip_len - 1:
+                base_offsets = np.arange(self.num_clips) * avg_interval
+                clip_offsets = (base_offsets + np.random.uniform(
+                    0, avg_interval, self.num_clips)).astype(np.int)
+            else:
+                clip_offsets = np.zeros((self.num_clips, ), dtype=np.int)
         else:
-            clip_offsets = np.zeros((self.num_clips, ), dtype=np.int)
+            avg_interval = (num_frames - ori_clip_len + 1) // self.num_clips
+
+            if avg_interval > 0:
+                base_offsets = np.arange(self.num_clips) * avg_interval
+                clip_offsets = base_offsets + np.random.randint(
+                    avg_interval, size=self.num_clips)
+            elif num_frames > max(self.num_clips, ori_clip_len):
+                clip_offsets = np.sort(
+                    np.random.randint(
+                        num_frames - ori_clip_len + 1, size=self.num_clips))
+            elif avg_interval == 0:
+                ratio = (num_frames - ori_clip_len + 1.0) / self.num_clips
+                clip_offsets = np.around(np.arange(self.num_clips) * ratio)
+            else:
+                clip_offsets = np.zeros((self.num_clips, ), dtype=np.int)
 
         return clip_offsets
 
@@ -333,21 +348,11 @@ class DenseSampleFrames(SampleFrames):
     """
 
     def __init__(self,
-                 clip_len,
-                 frame_interval=1,
-                 num_clips=1,
+                 *args,
                  sample_range=64,
                  num_sample_positions=10,
-                 temporal_jitter=False,
-                 out_of_bound_opt='loop',
-                 test_mode=False):
-        super().__init__(
-            clip_len,
-            frame_interval,
-            num_clips,
-            temporal_jitter,
-            out_of_bound_opt=out_of_bound_opt,
-            test_mode=test_mode)
+                 **kwargs):
+        super().__init__(*args, **kwargs)
         self.sample_range = sample_range
         self.num_sample_positions = num_sample_positions
 
diff --git a/tests/test_data/test_pipelines/test_loadings/test_sampling.py b/tests/test_data/test_pipelines/test_loadings/test_sampling.py
index 4e47424f74..2cd7a60116 100644
--- a/tests/test_data/test_pipelines/test_loadings/test_sampling.py
+++ b/tests/test_data/test_pipelines/test_loadings/test_sampling.py
@@ -26,6 +26,15 @@ def test_sample_frames(self):
                 clip_len=3, frame_interval=1, num_clips=5, start_index=1)
             SampleFrames(**config)
 
+        # Sample Frame with tail Frames
+        video_result = copy.deepcopy(self.video_results)
+        frame_result = copy.deepcopy(self.frame_results)
+        config = dict(
+            clip_len=3, frame_interval=1, num_clips=5, keep_tail_frames=True)
+        sample_frames = SampleFrames(**config)
+        sample_frames(video_result)
+        sample_frames(frame_result)
+
         # Sample Frame with no temporal_jitter
         # clip_len=3, frame_interval=1, num_clips=5
         video_result = copy.deepcopy(self.video_results)