diff --git a/tensorflow/lite/kernels/internal/reference/conv.h b/tensorflow/lite/kernels/internal/reference/conv.h
index d4bf46a86b8..b912ac1b3a4 100644
--- a/tensorflow/lite/kernels/internal/reference/conv.h
+++ b/tensorflow/lite/kernels/internal/reference/conv.h
@@ -59,28 +59,31 @@ inline void Conv(const ConvParams& params, const RuntimeShape& input_shape,
   const int output_width = output_shape.Dims(2);
   for (int batch = 0; batch < batches; ++batch) {
     for (int out_y = 0; out_y < output_height; ++out_y) {
+      const int in_y_origin = (out_y * stride_height) - pad_height;
       for (int out_x = 0; out_x < output_width; ++out_x) {
+        const int in_x_origin = (out_x * stride_width) - pad_width;
         for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
-          const int in_x_origin = (out_x * stride_width) - pad_width;
-          const int in_y_origin = (out_y * stride_height) - pad_height;
           float total = 0.f;
           for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+            const int in_y = in_y_origin + dilation_height_factor * filter_y;
             for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+              const int in_x = in_x_origin + dilation_width_factor * filter_x;
+
+              // Zero padding by omitting the areas outside the image.
+              const bool is_point_inside_image =
+                  (in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                  (in_y < input_height);
+
+              if (!is_point_inside_image) {
+                continue;
+              }
+
               for (int in_channel = 0; in_channel < input_depth; ++in_channel) {
-                const int in_x = in_x_origin + dilation_width_factor * filter_x;
-                const int in_y =
-                    in_y_origin + dilation_height_factor * filter_y;
-                // If the location is outside the bounds of the input image,
-                // use zero as a default value.
-                if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
-                    (in_y < input_height)) {
-                  float input_value = input_data[Offset(
-                      input_shape, batch, in_y, in_x, in_channel)];
-                  float filter_value =
-                      filter_data[Offset(filter_shape, out_channel, filter_y,
-                                         filter_x, in_channel)];
-                  total += (input_value * filter_value);
-                }
+                float input_value = input_data[Offset(input_shape, batch, in_y,
+                                                      in_x, in_channel)];
+                float filter_value = filter_data[Offset(
+                    filter_shape, out_channel, filter_y, filter_x, in_channel)];
+                total += (input_value * filter_value);
               }
             }
           }
@@ -139,29 +142,32 @@ inline void Conv(const ConvParams& params, const RuntimeShape& input_shape,
   const int output_width = output_shape.Dims(2);
   for (int batch = 0; batch < batches; ++batch) {
     for (int out_y = 0; out_y < output_height; ++out_y) {
+      const int in_y_origin = (out_y * stride_height) - pad_height;
       for (int out_x = 0; out_x < output_width; ++out_x) {
+        const int in_x_origin = (out_x * stride_width) - pad_width;
         for (int out_channel = 0; out_channel < output_depth; ++out_channel) {
-          const int in_x_origin = (out_x * stride_width) - pad_width;
-          const int in_y_origin = (out_y * stride_height) - pad_height;
           int32_t acc = 0;
           for (int filter_y = 0; filter_y < filter_height; ++filter_y) {
+            const int in_y = in_y_origin + dilation_height_factor * filter_y;
             for (int filter_x = 0; filter_x < filter_width; ++filter_x) {
+              const int in_x = in_x_origin + dilation_width_factor * filter_x;
+
+              // Zero padding by omitting the areas outside the image.
+              const bool is_point_inside_image =
+                  (in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
+                  (in_y < input_height);
+
+              if (!is_point_inside_image) {
+                continue;
+              }
+
               for (int in_channel = 0; in_channel < input_depth; ++in_channel) {
-                const int in_x = in_x_origin + dilation_width_factor * filter_x;
-                const int in_y =
-                    in_y_origin + dilation_height_factor * filter_y;
-                // If the location is outside the bounds of the input image,
-                // use zero as a default value.
-                if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) &&
-                    (in_y < input_height)) {
-                  int32_t input_val = input_data[Offset(
-                      input_shape, batch, in_y, in_x, in_channel)];
-                  int32_t filter_val =
-                      filter_data[Offset(filter_shape, out_channel, filter_y,
-                                         filter_x, in_channel)];
-                  acc +=
-                      (filter_val + filter_offset) * (input_val + input_offset);
-                }
+                int32_t input_val = input_data[Offset(input_shape, batch, in_y,
+                                                      in_x, in_channel)];
+                int32_t filter_val = filter_data[Offset(
+                    filter_shape, out_channel, filter_y, filter_x, in_channel)];
+                acc +=
+                    (filter_val + filter_offset) * (input_val + input_offset);
               }
             }
           }
@@ -258,5 +264,4 @@ inline void HybridConvPerChannel(
 }  // namespace reference_ops
 }  // namespace tflite
 
-
 #endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_CONV_H_