diff --git a/doc/source/whatsnew/v1.1.1.rst b/doc/source/whatsnew/v1.1.1.rst
index b37103910afab..98d67e930ccc0 100644
--- a/doc/source/whatsnew/v1.1.1.rst
+++ b/doc/source/whatsnew/v1.1.1.rst
@@ -22,6 +22,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.shift` with ``axis=1`` and heterogeneous dtypes (:issue:`35488`)
 - Fixed regression in ``.groupby(..).rolling(..)`` where a segfault would occur with ``center=True`` and an odd number of values (:issue:`35552`)
 - Fixed regression in :meth:`DataFrame.apply` where functions that altered the input in-place only operated on a single row (:issue:`35462`)
+- Fixed regression in :meth:`DataFrame.reset_index` would raise a ``ValueError`` on empty :class:`DataFrame` with a :class:`MultiIndex` with a ``datetime64`` dtype level (:issue:`35606`, :issue:`35657`)
 - Fixed regression where :meth:`DataFrame.merge_asof` would raise a ``UnboundLocalError`` when ``left_index`` , ``right_index`` and ``tolerance`` were set (:issue:`35558`)
 - Fixed regression in ``.groupby(..).rolling(..)`` where a custom ``BaseIndexer`` would be ignored (:issue:`35557`)
 
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 547d86f221b5f..1587dd8798ec3 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -4816,7 +4816,7 @@ def _maybe_casted_values(index, labels=None):
 
                 # we can have situations where the whole mask is -1,
                 # meaning there is nothing found in labels, so make all nan's
-                if mask.all():
+                if mask.size > 0 and mask.all():
                     dtype = index.dtype
                     fill_value = na_value_for_dtype(dtype)
                     values = construct_1d_arraylike_from_scalar(
diff --git a/pandas/tests/frame/methods/test_reset_index.py b/pandas/tests/frame/methods/test_reset_index.py
index da4bfa9be4881..b88ef0e6691cb 100644
--- a/pandas/tests/frame/methods/test_reset_index.py
+++ b/pandas/tests/frame/methods/test_reset_index.py
@@ -318,3 +318,33 @@ def test_reset_index_dtypes_on_empty_frame_with_multiindex(array, dtype):
     result = DataFrame(index=idx)[:0].reset_index().dtypes
     expected = Series({"level_0": np.int64, "level_1": np.float64, "level_2": dtype})
     tm.assert_series_equal(result, expected)
+
+
+def test_reset_index_empty_frame_with_datetime64_multiindex():
+    # https://github.com/pandas-dev/pandas/issues/35606
+    idx = MultiIndex(
+        levels=[[pd.Timestamp("2020-07-20 00:00:00")], [3, 4]],
+        codes=[[], []],
+        names=["a", "b"],
+    )
+    df = DataFrame(index=idx, columns=["c", "d"])
+    result = df.reset_index()
+    expected = DataFrame(
+        columns=list("abcd"), index=RangeIndex(start=0, stop=0, step=1)
+    )
+    expected["a"] = expected["a"].astype("datetime64[ns]")
+    expected["b"] = expected["b"].astype("int64")
+    tm.assert_frame_equal(result, expected)
+
+
+def test_reset_index_empty_frame_with_datetime64_multiindex_from_groupby():
+    # https://github.com/pandas-dev/pandas/issues/35657
+    df = DataFrame(dict(c1=[10.0], c2=["a"], c3=pd.to_datetime("2020-01-01")))
+    df = df.head(0).groupby(["c2", "c3"])[["c1"]].sum()
+    result = df.reset_index()
+    expected = DataFrame(
+        columns=["c2", "c3", "c1"], index=RangeIndex(start=0, stop=0, step=1)
+    )
+    expected["c3"] = expected["c3"].astype("datetime64[ns]")
+    expected["c1"] = expected["c1"].astype("float64")
+    tm.assert_frame_equal(result, expected)