diff --git a/include/tvm/topi/transform.h b/include/tvm/topi/transform.h
index 5c3734b6e4c0..eb1ad8bd622b 100644
--- a/include/tvm/topi/transform.h
+++ b/include/tvm/topi/transform.h
@@ -550,6 +550,8 @@ inline Array<Tensor> split(const Tensor& x, Array<PrimExpr> split_indices, int a
   return result;
 }
 
+// inline te::Tensor strided_slice_compute_common() {}
+
 /*!
  * \brief strided_slice of a tensor with dynamic begin/end/stride
  *
@@ -657,7 +659,7 @@ inline Tensor strided_slice_dynamic_input(const Tensor& input, const Array<Integ
 inline Tensor strided_slice_with_axes(const Tensor& x, const Array<Integer>& begin,
                                       const Array<Integer>& end, const Array<Integer>& strides,
                                       const Array<Integer>& axes, std::string slice_mode = "end",
-                                      std::string name = "T_strided_slice_dynamic_input",
+                                      std::string name = "T_strided_slice_with_axes",
                                       std::string tag = kInjective) {
   size_t src_tensor_dim = x->shape.size();
 
@@ -703,10 +705,12 @@ inline Tensor strided_slice_with_axes(const Tensor& x, const Array<Integer>& beg
   }
 
   // Compute
-  Array<PrimExpr> begin_expr;
-  Array<PrimExpr> strides_expr;
-
   Array<PrimExpr> out_shape;
+  for (size_t i = 0; i < src_tensor_dim; ++i) {
+    out_shape.push_back(x->shape[i]);
+  }
+
+  Array<PrimExpr> begin_expr, strides_expr;
   for (size_t i = 0; i < axes.size(); ++i) {
     int64_t begin_range = stride_vec[i] < 0 ? -1 : 0;
     ICHECK(x->shape[axes[i]]->IsInstance<tvm::IntImmNode>())
@@ -734,7 +738,7 @@ inline Tensor strided_slice_with_axes(const Tensor& x, const Array<Integer>& beg
     begin_expr.push_back(make_const(begin[0].dtype(), begin_i));
     strides_expr.push_back(
         make_const((strides.size() != 0 ? strides[0].dtype() : begin[0].dtype()), stride_vec[i]));
-    out_shape.push_back(slice_size);
+    out_shape.Set(axes[i], cast(out_shape[i].dtype(), PrimExpr(slice_size)));
   }
 
   return te::compute(
@@ -743,12 +747,12 @@ inline Tensor strided_slice_with_axes(const Tensor& x, const Array<Integer>& beg
         Array<PrimExpr> real_indices;
         for (size_t i = 0; i < src_tensor_dim; ++i) real_indices.push_back(indices[i]);
         for (size_t i = 0; i < axes.size(); ++i) {
-          PrimExpr ind = indices[axes[i]] * strides[i] + begin_expr[i];
+          PrimExpr ind = indices[axes[i]] * strides_expr[i] + begin_expr[i];
           real_indices.Set(axes[i], ind);
         }
         return x(real_indices);
       },
-      std::string{"T_strided_slice_with_axes"}, std::string{topi::kInjective});
+      name, tag);
 }
 
 /*!
diff --git a/python/tvm/relay/frontend/onnx.py b/python/tvm/relay/frontend/onnx.py
index 6671abb2e263..40958116517f 100644
--- a/python/tvm/relay/frontend/onnx.py
+++ b/python/tvm/relay/frontend/onnx.py
@@ -1359,7 +1359,7 @@ def has_static_axes():
             else:
                 strides_np = steps.data.asnumpy().astype("int64")
 
-            # return _op.strided_slice(inputs[0], list(begin_np), list(end_np), list(strides_np), axes=list(axes_np))
+            return _op.strided_slice(inputs[0], list(begin_np), list(end_np), list(strides_np), axes=list(axes_np))
 
         # Update the starts and ends according to axes if required.
         if axes is not None: