diff --git a/python/tvm/relay/frontend/tensorflow.py b/python/tvm/relay/frontend/tensorflow.py
index f65446691023..47bd0cdaeec8 100644
--- a/python/tvm/relay/frontend/tensorflow.py
+++ b/python/tvm/relay/frontend/tensorflow.py
@@ -603,7 +603,7 @@ def _impl(inputs, attr, params, mod):
         out = AttrCvt(
             op_name=_dimension_picker('conv',
                                       surfix="_transpose" if opname == 'conv_transpose' else ""),
-            ignores=['explicit_paddings'],
+            ignores=['explicit_paddings', 'Tshape'],
             transforms={
                 'kernel_shape': 'kernel_size',
                 'data_format': 'data_layout',
@@ -2046,6 +2046,7 @@ def _impl(inputs, attr, params, mod):
     'Conv2D'                            : _conv('conv'),
     'Conv2DBackpropInput'               : _conv('conv_transpose'),
     'Conv3D'                            : _conv3d('conv'),
+    'Conv3DBackpropInputV2'             : _conv3d('conv_transpose'),
     'Cos'                               : AttrCvt('cos'),
     'Cosh'                              : AttrCvt('cosh'),
     'CropAndResize'                     : _crop_and_resize(),
diff --git a/tests/python/frontend/tensorflow/test_forward.py b/tests/python/frontend/tensorflow/test_forward.py
index 252c4cd8904a..1a4294b52bfc 100644
--- a/tests/python/frontend/tensorflow/test_forward.py
+++ b/tests/python/frontend/tensorflow/test_forward.py
@@ -533,6 +533,92 @@ def test_forward_convolution3d():
     _test_convolution3d('conv', [4, 17, 17, 17, 12], [3, 3, 3, 12, 32], [1, 1, 1], [2, 2, 2], 'VALID', 'NDHWC')
 
 
+#######################################################################
+# Convolution3D Transpose
+# -----------------------
+
+def _test_convolution3d_transpose(data_shape, filter_shape, strides,
+                                  padding, output_shape, data_format='NCDHW'):
+    """ One iteration of 3D convolution transpose with given shapes and attributes """
+
+    dtype = 'float32'
+    data_array = np.random.uniform(size=data_shape).astype(dtype)
+    filter_array = np.random.uniform(size=filter_shape).astype(dtype)
+    if data_format == 'NDHWC':
+        strides = [1] + strides + [1]
+    else:
+        strides = [1, 1] + strides
+
+    with tf.Graph().as_default():
+        in_data = array_ops.placeholder(shape=data_shape, dtype=dtype)
+        in_filter = constant_op.constant(
+            filter_array, shape=filter_shape, dtype=dtype)
+
+        nn_ops.conv3d_transpose(in_data,
+                                in_filter,
+                                output_shape=output_shape,
+                                strides=strides,
+                                padding=padding,
+                                data_format=data_format)
+
+        compare_tf_with_tvm(data_array, 'Placeholder:0', 'conv3d_transpose:0', cuda_layout="NDHWC")
+
+
+def test_forward_convolution3d_transpose():
+    if is_gpu_available():
+        _test_convolution3d_transpose(data_shape=[1, 10, 8, 8, 8],
+                                      filter_shape=[1, 1, 1, 6, 10],
+                                      strides=[1, 1, 1],
+                                      padding='VALID',
+                                      output_shape=[1, 6, 8, 8, 8])
+
+        _test_convolution3d_transpose(data_shape=[4, 9, 8, 8, 8],
+                                      filter_shape=[1, 1, 1, 6, 9],
+                                      strides=[1, 1, 1],
+                                      padding='VALID',
+                                      output_shape=[4, 6, 8, 8, 8])
+
+        _test_convolution3d_transpose(data_shape=[1, 3, 8, 8, 8],
+                                      filter_shape=[1, 1, 1, 6, 3],
+                                      strides=[2, 2, 2],
+                                      padding='SAME',
+                                      output_shape=[1, 6, 15, 15, 15])
+
+        _test_convolution3d_transpose(data_shape=[1, 16, 8, 8, 8],
+                                      filter_shape=[3, 3, 3, 6, 16],
+                                      strides=[3, 3, 3],
+                                      padding='VALID',
+                                      output_shape=[1, 6, 24, 24, 24])
+
+    _test_convolution3d_transpose(data_shape=[1, 8, 8, 8, 10],
+                                  filter_shape=[1, 1, 1, 6, 10],
+                                  strides=[1, 1, 1],
+                                  padding='VALID',
+                                  output_shape=[1, 8, 8, 8, 6],
+                                  data_format='NDHWC')
+
+    _test_convolution3d_transpose(data_shape=[4, 8, 8, 8, 9],
+                                  filter_shape=[1, 1, 1, 6, 9],
+                                  strides=[1, 1, 1],
+                                  padding='VALID',
+                                  output_shape=[4, 8, 8, 8, 6],
+                                  data_format='NDHWC')
+
+    _test_convolution3d_transpose(data_shape=[1, 8, 8, 8, 3],
+                                  filter_shape=[1, 1, 1, 6, 3],
+                                  strides=[2, 2, 2],
+                                  padding='SAME',
+                                  output_shape=[1, 15, 15, 15, 6],
+                                  data_format='NDHWC')
+
+    _test_convolution3d_transpose(data_shape=[1, 8, 8, 8, 16],
+                                  filter_shape=[3, 3, 3, 6, 16],
+                                  strides=[3, 3, 3],
+                                  padding='VALID',
+                                  output_shape=[1, 24, 24, 24, 6],
+                                  data_format='NDHWC')
+
+
 #######################################################################
 # BiasAdd
 # -----------
@@ -3728,6 +3814,7 @@ def test_forward_spop():
     # NN
     test_forward_convolution()
     test_forward_convolution3d()
+    test_forward_convolution3d_transpose()
     test_forward_pooling()
     test_forward_concat_v2()
     test_forward_lrn()