diff --git a/python/tvm/relay/frontend/tensorflow.py b/python/tvm/relay/frontend/tensorflow.py
index af99447514d03..bc2b94840f470 100644
--- a/python/tvm/relay/frontend/tensorflow.py
+++ b/python/tvm/relay/frontend/tensorflow.py
@@ -857,6 +857,13 @@ def _impl(inputs, attr, params, mod):
             nmsed_boxes = _op.maximum(nmsed_boxes, _expr.const(0, dtype="float32"))
             nmsed_boxes = _op.minimum(nmsed_boxes, _expr.const(1, dtype="float32"))
 
+        # Fill in invalid entries with 0
+        box_range = _op.arange(_expr.const(0, dtype="int32"), max_total_size, dtype="int32")
+        box_range = _op.broadcast_to(_op.cast(box_range, "int64"), _op.shape_of(nmsed_scores))
+        valid_mask = _op.cast(_op.less(box_range, num_detections), "float32")
+        nmsed_scores = nmsed_scores * valid_mask
+        # nmsed_boxes = nmsed_boxes * _op.expand_dims(valid_mask, axis=2)
+
         return _expr.TupleWrapper(
             _expr.Tuple([nmsed_boxes, nmsed_scores, nmsed_classes, num_detections]), 4
         )
diff --git a/python/tvm/topi/cuda/nms.py b/python/tvm/topi/cuda/nms.py
index 971464ce26f2f..cc21d5ebc0669 100644
--- a/python/tvm/topi/cuda/nms.py
+++ b/python/tvm/topi/cuda/nms.py
@@ -1021,17 +1021,24 @@ def _collect_selected_indices_tf_ir(
     ib.scope_attr(tx, "thread_extent", nthread_tx)
     ib.scope_attr(bx, "thread_extent", nthread_bx)
     ib.scope_attr(by, "thread_extent", nthread_by)
+    zero = cast(0, "int64")
 
     with ib.new_scope():
         idx = bx * nthread_tx + tx
         idy = cast(by, "int64")
         batch_id = idy // num_class
         class_id = idy % num_class
+        offset = row_offsets[batch_id, class_id] + idx
+
         with ib.if_scope(idx < num_detections[batch_id, class_id]):
-            offset = row_offsets[batch_id, class_id]
-            collected_indices[batch_id, offset + idx, 0] = class_id
-            collected_indices[batch_id, offset + idx, 1] = cast(selected_indices[idy, idx], "int64")
-            collected_scores[batch_id, offset + idx] = selected_scores[idy, idx]
+            collected_indices[batch_id, offset, 0] = class_id
+            collected_indices[batch_id, offset, 1] = cast(selected_indices[idy, idx], "int64")
+            collected_scores[batch_id, offset] = selected_scores[idy, idx]
+        with ib.else_scope():
+            with ib.if_scope(idx < num_boxes):
+                collected_indices[batch_id, offset, 0] = zero
+                collected_indices[batch_id, offset, 1] = zero
+                collected_scores[batch_id, offset] = -1.0
 
     return ib.get()