diff --git a/python/tvm/relay/frontend/tflite.py b/python/tvm/relay/frontend/tflite.py
index 0ffd07e77d9e..acfa9148a756 100644
--- a/python/tvm/relay/frontend/tflite.py
+++ b/python/tvm/relay/frontend/tflite.py
@@ -60,6 +60,8 @@ def __init__(self, model, subgraph, exp_tab):
             'DEPTHWISE_CONV_2D': self.convert_depthwise_conv2d,
             'AVERAGE_POOL_2D': self.convert_average_pool2d,
             'RESHAPE': self.convert_reshape,
+            'RESIZE_BILINEAR': self.convert_resize_bilinear,
+            'RESIZE_NEAREST_NEIGHBOR': self.convert_resize_nearest_neighbor,
             'SOFTMAX': self.convert_softmax,
             'SQUEEZE': self.convert_squeeze,
             'MAX_POOL_2D': self.convert_max_pool2d,
@@ -225,6 +227,58 @@ def convert_reshape(self, op):
 
         return out
 
+    def _convert_resize(self, method, op):
+        """Generic method to Convert TFLite RESIZE operators"""
+        try:
+            from tflite.BuiltinOptions import BuiltinOptions
+            from tflite.Operator import Operator
+            from tflite.ResizeBilinearOptions import ResizeBilinearOptions
+            # ResizeNearestNeighborOptions was added in tflite v1.13
+            tflite_ver = 1120
+            if 'ResizeNearestNeighborOptions' in dir(BuiltinOptions):
+                from tflite.ResizeNearestNeighborOptions import ResizeNearestNeighborOptions
+                tflite_ver = 1130
+        except ImportError:
+            raise ImportError("The tflite package must be installed")
+
+        assert isinstance(op, Operator)
+        input_tensors = self.get_input_tensors(op)
+        assert len(input_tensors) == 2, "input tensors length should be 2"
+
+        # images, 4-D Tensor with shape NHWC.
+        input_tensor = input_tensors[0]
+        in_expr = self.get_expr(input_tensor.tensor_idx)
+
+        # size - 1-D int32 Tensor of 2 elements: new_height, new_width
+        target_size = tuple(self.get_tensor_value(input_tensors[1]))
+
+        # Options - align_corners (bool)
+        resize_options = None
+        align_corners = False
+        if method == "BILINEAR":
+            assert op.BuiltinOptionsType() == BuiltinOptions.ResizeBilinearOptions
+            resize_options = ResizeBilinearOptions()
+        elif tflite_ver >= 1130:
+            assert op.BuiltinOptionsType() == BuiltinOptions.ResizeNearestNeighborOptions
+            resize_options = ResizeNearestNeighborOptions()
+
+        if resize_options is not None:
+            op_options = op.BuiltinOptions()
+            resize_options.Init(op_options.Bytes, op_options.Pos)
+            align_corners = resize_options.AlignCorners()
+
+        # Use layout NHWC
+        out = _op.image.resize(in_expr, target_size, "NHWC", method, align_corners)
+        return out
+
+    def convert_resize_bilinear(self, op):
+        """Convert TFLite RESIZE_BILINEAR"""
+        return self._convert_resize("BILINEAR", op)
+
+    def convert_resize_nearest_neighbor(self, op):
+        """Convert TFLite RESIZE_NEAREST_NEIGHBOR"""
+        return self._convert_resize("NEAREST_NEIGHBOR", op)
+
     def convert_logistic(self, op):
         """Convert TFLite LOGISTIC"""
         try:
diff --git a/tests/python/frontend/tflite/test_forward.py b/tests/python/frontend/tflite/test_forward.py
index 795a08966e1d..0a011a6e709b 100644
--- a/tests/python/frontend/tflite/test_forward.py
+++ b/tests/python/frontend/tflite/test_forward.py
@@ -289,6 +289,37 @@ def test_forward_reshape():
     _test_reshape(np.arange(6), [-1])
 
 
+#######################################################################
+# Resize
+# ------
+
+def _test_resize(tf_resize_op, data, align_corners):
+    """ One iteration of Resize """
+
+    assert len(data) == 2
+
+    # Test with tensor and constant
+    with tf.Graph().as_default():
+        images_tensor = array_ops.placeholder(shape=data[0].shape, dtype=data[0].dtype, name='in')
+        size = ops.convert_to_tensor(data[1], dtype=data[1].dtype)
+        out_tensor = tf_resize_op(images=images_tensor, size=size, align_corners=align_corners)
+        compare_tflite_with_tvm([data[0]], ['in:0'], [images_tensor], [out_tensor])
+
+
+def test_all_resize():
+    """ Resize """
+    data = [np.random.rand(1, 16, 16, 3).astype("float32"), np.array([8, 8], dtype=np.int32)]
+    ### RESIZE_BILINEAR
+    _test_resize(tf.image.resize_bilinear, data, align_corners=False)
+    _test_resize(tf.image.resize_bilinear, data, align_corners=True)
+    ### RESIZE_NEAREST_NEIGHBOR (was added in v1.13)
+    # According to topi resize.h
+    # Align corners not supported for nearest neighbour
+    from tflite.BuiltinOperator import BuiltinOperator
+    if 'RESIZE_NEAREST_NEIGHBOR' in dir(BuiltinOperator()):
+        _test_resize(tf.image.resize_nearest_neighbor, data, align_corners=False)
+
+
 #######################################################################
 # Concatenation
 # -------------
@@ -651,6 +682,7 @@ def test_forward_ssd_mobilenet_v1():
     test_forward_concatenation()
     test_forward_pad()
     test_forward_reshape()
+    test_all_resize()
     test_forward_squeeze()
 
     # NN
diff --git a/topi/include/topi/image/resize.h b/topi/include/topi/image/resize.h
index 287ff9406618..0119aed3aff0 100644
--- a/topi/include/topi/image/resize.h
+++ b/topi/include/topi/image/resize.h
@@ -384,7 +384,7 @@ inline Tensor resize_bilinear(const Tensor& input,
 * \param shape Output shape to resize to.
 * \param layout input layout
 * \param align_corners To preserve centers of 4 corner pixels
-* \param mode Angorithm to use (NEAREST_NEIGHBOR / BILINEAR)
+* \param mode Algorithm to use (NEAREST_NEIGHBOR / BILINEAR)
 * \param name Name of the operation
 * \param tag The tag to mark the operation
 *
diff --git a/topi/include/topi/nn/upsampling.h b/topi/include/topi/nn/upsampling.h
index eb75d5dd8d92..d7551afbe04f 100644
--- a/topi/include/topi/nn/upsampling.h
+++ b/topi/include/topi/nn/upsampling.h
@@ -43,7 +43,7 @@ using namespace topi::image;
 * \param input The input tensor.
 * \param shape Output shape to upsample.
 * \param layout input layout
-* \param mode Angorithm to use (NEAREST_NEIGHBOR / BILINEAR)
+* \param mode Algorithm to use (NEAREST_NEIGHBOR / BILINEAR)
 * \param name Name of the operation
 * \param tag The tag to mark the operation
 *