diff --git a/chainercv/datasets/__init__.py b/chainercv/datasets/__init__.py
index 6ecea75ca5..da0d25a635 100644
--- a/chainercv/datasets/__init__.py
+++ b/chainercv/datasets/__init__.py
@@ -28,7 +28,6 @@
 from chainercv.datasets.sbd.sbd_instance_segmentation_dataset import SBDInstanceSegmentationDataset  # NOQA
 from chainercv.datasets.sbd.sbd_utils import sbd_instance_segmentation_label_names  # NOQA
 from chainercv.datasets.siamese_dataset import SiameseDataset  # NOQA
-from chainercv.datasets.transform_dataset import TransformDataset  # NOQA
 from chainercv.datasets.voc.voc_bbox_dataset import VOCBboxDataset  # NOQA
 from chainercv.datasets.voc.voc_instance_segmentation_dataset import VOCInstanceSegmentationDataset  # NOQA
 from chainercv.datasets.voc.voc_semantic_segmentation_dataset import VOCSemanticSegmentationDataset  # NOQA
diff --git a/chainercv/datasets/transform_dataset.py b/chainercv/datasets/transform_dataset.py
deleted file mode 100644
index 8e4f878cc7..0000000000
--- a/chainercv/datasets/transform_dataset.py
+++ /dev/null
@@ -1,61 +0,0 @@
-import warnings
-
-
-class TransformDataset(object):
-
-    """Dataset that indexes data of a base dataset and transforms it.
-
-    This dataset wraps a base dataset by modifying the behavior of the base
-    dataset's :meth:`__getitem__`. Arrays returned by :meth:`__getitem__` of
-    the base dataset with an integer index are transformed by the given
-    function :obj:`transform`.
-
-    The function :obj:`transform` takes, as an argument, :obj:`in_data`, which
-    is output of the base dataset's :meth:`__getitem__`, and returns
-    transformed arrays as output. Please see the following example.
-
-    >>> from chainer.datasets import get_mnist
-    >>> from chainercv.datasets import TransformDataset
-    >>> dataset, _ = get_mnist()
-    >>> def transform(in_data):
-    >>>     img, label = in_data
-    >>>     img -= 0.5  # scale to [-0.5, -0.5]
-    >>>     return img, label
-    >>> dataset = TransformDataset(dataset, transform)
-
-    .. note::
-
-        The index used to access data is either an integer or a slice. If it
-        is a slice, the base dataset is assumed to return a list of outputs
-        each corresponding to the output of the integer indexing.
-
-    .. note::
-        This class is deprecated. Please use
-        :class:`chainer.datasets.TransformDataset` instead.
-
-    Args:
-        dataset: Underlying dataset. The index of this dataset corresponds
-            to the index of the base dataset.
-        transform (callable): A function that is called to transform values
-            returned by the underlying dataset's :meth:`__getitem__`.
-
-    """
-
-    def __init__(self, dataset, transform):
-        warnings.warn(
-            'chainercv.datasets.TransformDataset is deprecated. '
-            'Please use chainer.datasets.TransformDataset instead.',
-            DeprecationWarning)
-
-        self._dataset = dataset
-        self._transform = transform
-
-    def __getitem__(self, index):
-        in_data = self._dataset[index]
-        if isinstance(index, slice):
-            return [self._transform(in_data_elem) for in_data_elem in in_data]
-        else:
-            return self._transform(in_data)
-
-    def __len__(self):
-        return len(self._dataset)
diff --git a/tests/datasets_tests/test_transform_dataset.py b/tests/datasets_tests/test_transform_dataset.py
deleted file mode 100644
index 3ef6b47ee9..0000000000
--- a/tests/datasets_tests/test_transform_dataset.py
+++ /dev/null
@@ -1,27 +0,0 @@
-import unittest
-
-import numpy as np
-
-from chainer import testing
-from chainercv.datasets import TransformDataset
-
-
-class TestTransformDataset(unittest.TestCase):
-
-    def test_transform_dataset(self):
-        dataset = np.random.uniform(size=(10, 3, 32, 32))
-        first_img = dataset[0]
-
-        def transform(in_data):
-            return in_data * 3
-
-        transformed_dataset = TransformDataset(dataset, transform)
-        out = transformed_dataset[0]
-        np.testing.assert_equal(out, first_img * 3)
-
-        outs = transformed_dataset[:2]
-        np.testing.assert_equal(
-            [transform(elem) for elem in dataset[:2]], outs)
-
-
-testing.run_module(__name__, __file__)