diff --git a/src/operator/nn/convolution.cu b/src/operator/nn/convolution.cu
index 65a320ded169..9f61212d5c78 100644
--- a/src/operator/nn/convolution.cu
+++ b/src/operator/nn/convolution.cu
@@ -89,8 +89,11 @@ void ConvolutionCompute<gpu>(const nnvm::NodeAttrs& attrs,
   const ConvolutionParam& param = nnvm::get<ConvolutionParam>(attrs.parsed);
   int dtype = inputs[conv::kData].type_flag_;
 
-  // If 1D convolution, use MXNet implementation
-  if (param.kernel.ndim() == 1) {
+#if CUDNN_MAJOR < 5
+  if (param_.layout.value() != kNCW &&
+      param_.layout.value() != kNCHW &&
+      param_.layout.value() != kNCDHW) {
+    // Need CuDNN > 5.0 for layout support. use MXNet implementation
     MSHADOW_REAL_TYPE_SWITCH(dtype, DType, {
       ConvolutionOp<gpu, DType> op;
       op.Init(param);
@@ -98,6 +101,8 @@ void ConvolutionCompute<gpu>(const nnvm::NodeAttrs& attrs,
     })
     return;
   }
+#endif
+
 #if MXNET_USE_CUDNN == 0 || CUDNN_MAJOR < 7
   if (param.num_filter == param.num_group &&
       param.layout.value() == mshadow::kNCHW &&
@@ -162,8 +167,11 @@ void ConvolutionGradCompute<gpu>(const nnvm::NodeAttrs& attrs,
   const std::vector<TBlob> &in_grad = outputs;
   int dtype = out_grad.type_flag_;
 
-  // If 1D convolution, use MXNet implementation
-  if (param.kernel.ndim() == 1) {
+#if CUDNN_MAJOR < 5
+  if (param_.layout.value() != kNCW &&
+      param_.layout.value() != kNCHW &&
+      param_.layout.value() != kNCDHW) {
+    // Need CuDNN > 5.0 for layout support. use MXNet implementation
     MSHADOW_REAL_TYPE_SWITCH(dtype, DType, {
       ConvolutionOp<gpu, DType> op;
       op.Init(param);
@@ -171,6 +179,7 @@ void ConvolutionGradCompute<gpu>(const nnvm::NodeAttrs& attrs,
     })
     return;
   }
+#endif
 #if MXNET_USE_CUDNN == 0 || CUDNN_MAJOR < 7
   if (param.num_filter == param.num_group &&
       param.layout.value() == mshadow::kNCHW &&