diff --git a/autograd/numpy/numpy_boxes.py b/autograd/numpy/numpy_boxes.py
index b9c73963..cc913449 100644
--- a/autograd/numpy/numpy_boxes.py
+++ b/autograd/numpy/numpy_boxes.py
@@ -18,6 +18,9 @@ class ArrayBox(Box):
     def __getitem__(A, idx):
         return A[idx]
 
+    def item(self):
+        return self[(0,) * len(self.shape)]
+
     # Constants w.r.t float data just pass though
     shape = property(lambda self: self._value.shape)
     ndim = property(lambda self: self._value.ndim)
diff --git a/autograd/numpy/numpy_wrapper.py b/autograd/numpy/numpy_wrapper.py
index baa0aed3..5f37bdeb 100644
--- a/autograd/numpy/numpy_wrapper.py
+++ b/autograd/numpy/numpy_wrapper.py
@@ -65,10 +65,23 @@ def column_stack(tup):
     return concatenate(arrays, 1)
 
 
+def _maybe_unwrap(a):
+    """Unwrap scalar arrays that do not contain sequences."""
+    from autograd.numpy.numpy_boxes import ArrayBox
+
+    if not a.shape:  # it is a scalar array
+        if isinstance(a, ArrayBox):
+            if not isinstance(a._value, (list, tuple)):
+                return a.item()
+        else:
+            return a.item()
+    return a
+
+
 def array(A, *args, **kwargs):
     t = builtins.type(A)
     if t in (list, tuple):
-        return array_from_args(args, kwargs, *map(array, A))
+        return array_from_args(args, kwargs, *map(_maybe_unwrap, map(array, A)))
     else:
         return _array_from_scalar_or_array(args, kwargs, A)
 
diff --git a/tests/test_misc.py b/tests/test_misc.py
index 5cffd3e5..f2945dd3 100644
--- a/tests/test_misc.py
+++ b/tests/test_misc.py
@@ -106,3 +106,63 @@ def test_flatten_complex():
     val = 1 + 1j
     flat, unflatten = flatten(val)
     assert np.all(val == unflatten(flat))
+
+
+### Some tests for retrieval of objects from object-like arrays
+
+
+def test_object_array():
+    x = object()
+    a = np.array([x])
+    assert a.item() is x
+
+
+# Nested lists of objects and object arrays
+def test_object_array_nested():
+    x = object()
+    y = object()
+    a = np.array([[x], [y]])
+    ab = np.array([[x, y], [y, x]])
+
+    assert a[0, 0] is x
+    assert a[1, 0] is y
+
+    assert ab[0, 0] is x
+    assert ab[0, 1] is y
+    assert ab[1, 0] is y
+    assert ab[1, 1] is x
+
+    # Test mixed nesting; we use object arrays
+    # for inhomogeneous shapes
+    b = np.array([x, [y]], dtype=object)
+    assert b[0] is x
+    assert b[1][0] is y
+
+
+def test_zero_dim_arrays():
+    # 1. numeric scalar array
+    x = np.array(5)
+    arr = np.array([x])
+    assert arr[0] == 5
+
+    # 2. boolean scalar array
+    y = np.array(True)
+    arr2 = np.array([y])
+    assert arr2[0] == True  # noqa: E712 because np.True_ is not a bool
+
+
+def test_mixed_object_arrays():
+    x = object()
+    y = "string"
+    z = 42
+    arr = np.array([x, y, z])
+    assert arr[0] is x
+    assert arr[1] == "string"
+    assert arr[2] == 42
+
+
+def test_object_array_empty():
+    a = np.array([])
+    assert a.shape == (0,)
+    b = np.array([[]])
+    assert b.shape == (1, 0)