diff --git a/pandera/decorators.py b/pandera/decorators.py
index f4afee84..a36bb597 100644
--- a/pandera/decorators.py
+++ b/pandera/decorators.py
@@ -258,41 +258,29 @@ def _wrapper(*args, **kwargs):
                         pos_args[obj_getter], *validate_args
                     )
                     args = list(pos_args.values())
-            elif obj_getter is None and kwargs:
-                # get the first key in the same order specified in the
-                # function argument.
-                args_names = _get_fn_argnames(wrapped)
-
-                try:
-                    kwargs[args_names[0]] = schema.validate(
-                        kwargs[args_names[0]], *validate_args
-                    )
-                except errors.SchemaError as e:
-                    _handle_schema_error(
-                        "check_input",
-                        wrapped,
-                        schema,
-                        kwargs[args_names[0]],
-                        e,
-                    )
-            elif obj_getter is None and args:
+            elif obj_getter is None:
                 try:
-                    _fn = (
-                        wrapped
-                        if not hasattr(wrapped, "__wrapped__")
-                        else wrapped.__wrapped__
-                    )
+                    _fn = _unwrap_fn(wrapped)
+                    obj_arg_name, *_ = _get_fn_argnames(wrapped)
                     arg_spec_args = inspect.getfullargspec(_fn).args
-                    if arg_spec_args[0] in ("self", "cls"):
-                        arg_idx = 0 if len(args) == 1 else 1
+
+                    arg_idx = arg_spec_args.index(obj_arg_name)
+
+                    if obj_arg_name in kwargs:
+                        obj = kwargs[obj_arg_name]
+                        kwargs[obj_arg_name] = schema.validate(
+                            obj, *validate_args
+                        )
+                    elif obj_arg_name in pos_args:
+                        obj = args[arg_idx]
+                        args[arg_idx] = schema.validate(obj, *validate_args)
                     else:
-                        arg_idx = 0
-                    args[arg_idx] = schema.validate(
-                        args[arg_idx], *validate_args
-                    )
+                        raise ValueError(
+                            f"argument {obj_arg_name} not found in args or kwargs"
+                        )
                 except errors.SchemaError as e:
                     _handle_schema_error(
-                        "check_input", wrapped, schema, args[0], e
+                        "check_input", wrapped, schema, obj, e
                     )
             else:
                 raise TypeError(
diff --git a/tests/core/test_decorators.py b/tests/core/test_decorators.py
index e63eccb6..c3b7360b 100644
--- a/tests/core/test_decorators.py
+++ b/tests/core/test_decorators.py
@@ -348,6 +348,25 @@ def _assert_expectation(result_df):
     )
 
 
+class DfModel(DataFrameModel):
+    col: int
+
+
+# pylint: disable=unused-argument
+@check_input(DfModel.to_schema())
+def fn_with_check_input(data: DataFrame[DfModel], *, kwarg: bool = False):
+    return data
+
+
+def test_check_input_on_fn_with_kwarg():
+    """
+    That that a check_input correctly validates a function where the first arg
+    is the dataframe and the function has other kwargs.
+    """
+    df = pd.DataFrame({"col": [1]})
+    fn_with_check_input(df, kwarg=True)
+
+
 def test_check_io() -> None:
     # pylint: disable=too-many-locals
     """Test that check_io correctly validates/invalidates data."""
@@ -777,13 +796,13 @@ def test_check_types_with_literal_type(arg_examples):
     """Test that using typing module types works with check_types"""
 
     for example in arg_examples:
-        arg_type = Literal[example]
+        arg_type = Literal[example]  # type: ignore
 
         @check_types
         def transform_with_literal(
             df: DataFrame[InSchema],
             # pylint: disable=unused-argument,cell-var-from-loop
-            arg: arg_type,
+            arg: arg_type,  # type: ignore
         ) -> DataFrame[OutSchema]:
             return df.assign(b=100)  # type: ignore