diff --git a/paddle/fluid/operators/math/im2col.cc b/paddle/fluid/operators/math/im2col.cc
index a50b9ace39249f4f899a46e171bbdced033b46bc..1a42ef12647cc397c0642808987425a9677127a2 100644
--- a/paddle/fluid/operators/math/im2col.cc
+++ b/paddle/fluid/operators/math/im2col.cc
@@ -40,22 +40,46 @@ class Im2ColFunctor<paddle::operators::math::ColFormat::kCFO,
     int im_width = im.dims()[2];
     int filter_height = col->dims()[1];
     int filter_width = col->dims()[2];
-    int col_height = col->dims()[3];
-    int col_width = col->dims()[4];
+    int output_height = col->dims()[3];
+    int output_width = col->dims()[4];
 
     int channels_col = im_channels * filter_height * filter_width;
 
     const T* im_data = im.data<T>();
     T* col_data = col->data<T>();
+    // TODO(TJ): change me to template
+    // further optimaze:
+    // 1. padding != 1
+    // 2. could also support stride_h != 1
+    if (stride[0] == 1 && stride[1] == 1 && dilation[0] == 1 &&
+        dilation[1] == 1 && padding[0] == 0 && padding[1] == 0) {
+      int col_matrix_width = output_width * output_height;
+      for (int oh = 0; oh < output_height; ++oh) {
+        const T* im_data_start = im_data + oh * im_width;
+        T* dst_data = col_data + oh * output_width;
+        for (int ic = 0; ic < im_channels; ++ic) {
+          const T* src_data = im_data_start + ic * im_height * im_width;
+          for (int kh = 0; kh < filter_height; ++kh) {
+            for (int kw = 0; kw < filter_width; ++kw) {
+              std::memcpy(dst_data, src_data + kw, sizeof(T) * output_width);
+              dst_data = dst_data + col_matrix_width;
+            }
+            src_data = src_data + im_width;
+          }
+        }
+      }
+      return;
+    }
+
     for (int c = 0; c < channels_col; ++c) {
       int w_offset = c % filter_width;
       int h_offset = (c / filter_width) % filter_height;
       int c_im = c / (filter_width * filter_height);
-      for (int h = 0; h < col_height; ++h) {
+      for (int h = 0; h < output_height; ++h) {
         int im_row_idx = h * stride[0] - padding[0] + h_offset * dilation[0];
-        for (int w = 0; w < col_width; ++w) {
+        for (int w = 0; w < output_width; ++w) {
           int im_col_idx = w * stride[1] - padding[1] + w_offset * dilation[1];
-          int col_idx = (c * col_height + h) * col_width + w;
+          int col_idx = (c * output_height + h) * output_width + w;
           int im_idx = (im_row_idx + c_im * im_height) * im_width + im_col_idx;
 
           col_data[col_idx] = (im_row_idx < 0 || im_row_idx >= im_height ||