diff --git a/nnvm/python/nnvm/frontend/darknet.py b/nnvm/python/nnvm/frontend/darknet.py
index 50625b4b17a4..3a197a416219 100644
--- a/nnvm/python/nnvm/frontend/darknet.py
+++ b/nnvm/python/nnvm/frontend/darknet.py
@@ -673,6 +673,31 @@ def _handle_darknet_rnn_layers(self, layer_num, sym):
             self._sym_array[layer_num] = sym
             processed = True
 
+        elif LAYERTYPE.CRNN == layer.type:
+            attr.update({'n' : layer.n})
+            attr.update({'batch' : layer.batch})
+            attr.update({'num_hidden' : str(layer.outputs)})
+
+            state = self._get_rnn_state_buffer(layer)
+
+            for _ in range(layer.steps):
+                input_layer = layer.input_layer
+                sym = self._get_darknet_rnn_attrs(input_layer, sym)
+
+                self_layer = layer.self_layer
+                state = self._get_darknet_rnn_attrs(self_layer, state)
+
+                op_name, new_attrs = 'elemwise_add', {}
+                new_inputs = _as_list([sym, state])
+                state = _darknet_get_nnvm_op(op_name)(*new_inputs, **new_attrs)
+                self._outs.append(state)
+
+                output_layer = layer.output_layer
+                sym = self._get_darknet_rnn_attrs(output_layer, state)
+
+            self._sym_array[layer_num] = sym
+            processed = True
+
         return processed, sym
 
     def from_darknet(self):
diff --git a/nnvm/tests/python/frontend/darknet/test_forward.py b/nnvm/tests/python/frontend/darknet/test_forward.py
index 961da238452c..e68aed085664 100644
--- a/nnvm/tests/python/frontend/darknet/test_forward.py
+++ b/nnvm/tests/python/frontend/darknet/test_forward.py
@@ -324,6 +324,31 @@ def test_forward_rnn():
     test_rnn_forward(net)
     LIB.free_network(net)
 
+def test_forward_crnn():
+    '''test softmax layer'''
+    net = LIB.make_network(1)
+    batch = 1
+    c = 3
+    h = 224
+    w = 224
+    hidden_filters = c
+    output_filters = c
+    steps = 1
+    activation = 0
+    batch_normalize = 0
+    inputs = 256
+    outputs = 256
+    layer_1 = LIB.make_crnn_layer(batch, h, w, c, hidden_filters, output_filters,
+                                  steps, activation, batch_normalize)
+    net.layers[0] = layer_1
+    net.inputs = inputs
+    net.outputs = output_filters * h * w
+    net.w = w
+    net.h = h
+    LIB.resize_network(net, net.w, net.h)
+    test_forward(net)
+    LIB.free_network(net)
+
 def test_forward_activation_logistic():
     '''test logistic activation layer'''
     net = LIB.make_network(1)
@@ -369,4 +394,5 @@ def test_forward_activation_logistic():
     test_forward_region()
     test_forward_elu()
     test_forward_rnn()
+    test_forward_crnn()
     test_forward_activation_logistic()
\ No newline at end of file