diff --git a/lite/valor_lite/semantic_segmentation/computation.py b/lite/valor_lite/semantic_segmentation/computation.py
index 556a0ef9b..807c2bde6 100644
--- a/lite/valor_lite/semantic_segmentation/computation.py
+++ b/lite/valor_lite/semantic_segmentation/computation.py
@@ -31,9 +31,6 @@ def compute_intermediate_confusion_matrices(
         A 2-D confusion matrix with shape (n_labels + 1, n_labels + 1).
     """
 
-    n_gt_labels = groundtruth_labels.size
-    n_pd_labels = prediction_labels.size
-
     groundtruth_counts = groundtruths.sum(axis=1)
     prediction_counts = predictions.sum(axis=1)
 
@@ -42,33 +39,23 @@ def compute_intermediate_confusion_matrices(
     ).sum()
 
     intersection_counts = np.logical_and(
-        groundtruths.reshape(n_gt_labels, 1, -1),
-        predictions.reshape(1, n_pd_labels, -1),
+        groundtruths[:, None, :],
+        predictions[None, :, :],
     ).sum(axis=2)
-
     intersected_groundtruth_counts = intersection_counts.sum(axis=1)
     intersected_prediction_counts = intersection_counts.sum(axis=0)
 
     confusion_matrix = np.zeros((n_labels + 1, n_labels + 1), dtype=np.int32)
     confusion_matrix[0, 0] = background_counts
-    for gidx in range(n_gt_labels):
-        gt_label_idx = groundtruth_labels[gidx]
-        for pidx in range(n_pd_labels):
-            pd_label_idx = prediction_labels[pidx]
-            confusion_matrix[
-                gt_label_idx + 1,
-                pd_label_idx + 1,
-            ] = intersection_counts[gidx, pidx]
-
-            if gidx == 0:
-                confusion_matrix[0, pd_label_idx + 1] = (
-                    prediction_counts[pidx]
-                    - intersected_prediction_counts[pidx]
-                )
-
-        confusion_matrix[gt_label_idx + 1, 0] = (
-            groundtruth_counts[gidx] - intersected_groundtruth_counts[gidx]
-        )
+    confusion_matrix[
+        np.ix_(groundtruth_labels + 1, prediction_labels + 1)
+    ] = intersection_counts
+    confusion_matrix[0, prediction_labels + 1] = (
+        prediction_counts - intersected_prediction_counts
+    )
+    confusion_matrix[groundtruth_labels + 1, 0] = (
+        groundtruth_counts - intersected_groundtruth_counts
+    )
 
     return confusion_matrix