diff --git a/mediapipe/calculators/tensorflow/BUILD b/mediapipe/calculators/tensorflow/BUILD
index 0f8f8706..4aec15dc 100644
--- a/mediapipe/calculators/tensorflow/BUILD
+++ b/mediapipe/calculators/tensorflow/BUILD
@@ -1054,6 +1054,7 @@ cc_test(
         "//mediapipe/framework:calculator_framework",
         "//mediapipe/framework:calculator_runner",
         "//mediapipe/framework/port:gtest_main",
+        "//mediapipe/util:packet_test_util",
         "@org_tensorflow//tensorflow/core:framework",
         "@org_tensorflow//tensorflow/core:protos_all_cc",
     ],
diff --git a/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator.cc b/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator.cc
index cd807b87..ec7cd70f 100644
--- a/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator.cc
+++ b/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator.cc
@@ -102,7 +102,7 @@ absl::Status TensorToVectorFloatCalculator::Process(CalculatorContext* cc) {
     }
     auto output =
         absl::make_unique<std::vector<float>>(input_tensor.NumElements());
-    const auto& tensor_values = input_tensor.flat<float>();
+    const auto& tensor_values = input_tensor.unaligned_flat<float>();
     for (int i = 0; i < input_tensor.NumElements(); ++i) {
       output->at(i) = tensor_values(i);
     }
diff --git a/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator_test.cc b/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator_test.cc
index 69d3af60..98ba4f02 100644
--- a/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator_test.cc
+++ b/mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator_test.cc
@@ -16,6 +16,7 @@
 #include "mediapipe/framework/calculator_framework.h"
 #include "mediapipe/framework/calculator_runner.h"
 #include "mediapipe/framework/port/gtest.h"
+#include "mediapipe/util/packet_test_util.h"
 #include "tensorflow/core/framework/tensor.h"
 #include "tensorflow/core/framework/types.pb.h"
 
@@ -129,5 +130,28 @@ TEST_F(TensorToVectorFloatCalculatorTest, FlattenShouldTakeAllDimensions) {
   }
 }
 
+TEST_F(TensorToVectorFloatCalculatorTest, AcceptsUnalignedTensors) {
+  SetUpRunner(/*tensor_is_2d=*/false, /*flatten_nd=*/false);
+
+  const tf::TensorShape tensor_shape(std::vector<tf::int64>{2, 5});
+  tf::Tensor tensor(tf::DT_FLOAT, tensor_shape);
+  auto slice = tensor.Slice(1, 1).flat<float>();
+  for (int i = 0; i < 5; ++i) {
+    slice(i) = i;
+  }
+
+  auto input_tensor = tensor.SubSlice(1);
+  // Ensure that the input tensor is unaligned.
+  ASSERT_FALSE(input_tensor.IsAligned());
+  runner_->MutableInputs()->Index(0).packets.push_back(
+      MakePacket<tf::Tensor>(input_tensor).At(Timestamp(5)));
+
+  ASSERT_TRUE(runner_->Run().ok());
+
+  EXPECT_THAT(runner_->Outputs().Index(0).packets,
+              ElementsAre(PacketContainsTimestampAndPayload<std::vector<float>>(
+                  Timestamp(5), std::vector<float>({0, 1, 2, 3, 4}))));
+}
+
 }  // namespace
 }  // namespace mediapipe