diff --git a/src/spatialdata_plot/pl/utils.py b/src/spatialdata_plot/pl/utils.py
index dd0daee6..968fbe53 100644
--- a/src/spatialdata_plot/pl/utils.py
+++ b/src/spatialdata_plot/pl/utils.py
@@ -1078,6 +1078,13 @@ def _set_color_source_vec(
         table_name=table_name,
     )
 
+    # When both the element's own dataframe and the chosen table contain a
+    # column with this name, an explicit `table_name=` resolves the ambiguity —
+    # keep only the table origin and skip the multi-origin error below.
+    explicit_table_shadows_df = table_name is not None and any(o.origin == "df" for o in origins)
+    if explicit_table_shadows_df:
+        origins = [o for o in origins if o.origin != "df"]
+
     if len(origins) > 1:
         raise ValueError(
             f"Color key '{value_to_plot}' for element '{element_name}' was found in multiple locations: {origins}. "
@@ -1094,6 +1101,15 @@ def _set_color_source_vec(
             )
         if preloaded_color_data is not None:
             color_source_vector = preloaded_color_data
+        elif explicit_table_shadows_df:
+            # Pass the table as `element` so upstream `get_values` skips the
+            # element-column lookup and avoids the multi-origin error.
+            color_source_vector = get_values(
+                value_key=value_to_plot,
+                element=sdata[table_name],
+                element_name=element_name,
+                table_layer=table_layer,
+            )[value_to_plot]
         else:
             color_source_vector = get_values(
                 value_key=value_to_plot,
@@ -3170,9 +3186,9 @@ def _validate_col_for_column_table(
     if col_for_color is None:
         return None, None
 
-    if not labels and col_for_color in sdata[element_name].columns:
-        table_name = None
-    elif table_name is not None:
+    if not labels and col_for_color in sdata[element_name].columns and table_name is None:
+        return col_for_color, None
+    if table_name is not None:
         tables = get_element_annotators(sdata, element_name)
         if table_name not in tables:
             logger.warning(f"Table '{table_name}' does not annotate element '{element_name}'.")
diff --git a/tests/pl/test_utils.py b/tests/pl/test_utils.py
index 467a5efe..7f342ff7 100644
--- a/tests/pl/test_utils.py
+++ b/tests/pl/test_utils.py
@@ -420,3 +420,41 @@ def test_color_column_collision_on_annotating_table_raises():
         sdata.pl.render_shapes("s", color="orange")
 
     sdata.pl.render_shapes("s", color="#ffa500")
+
+
+def test_explicit_table_name_honored_when_element_has_same_column():
+    # regression test for #620: explicit table_name= must not be silently
+    # discarded when the element has a same-named column with different values.
+    shapes = ShapesModel.parse(
+        gpd.GeoDataFrame(
+            {
+                "geometry": [Point(5, 5), Point(15, 5)],
+                "radius": [2.0, 2.0],
+                "cat": pd.Categorical(["X", "Y"]),
+            }
+        )
+    )
+    obs = pd.DataFrame(
+        {
+            "instance_id": [0, 1],
+            "region": pd.Categorical(["s1", "s1"]),
+            "cat": pd.Categorical(["A", "B"]),
+        }
+    )
+    table = TableModel.parse(
+        AnnData(X=np.zeros((2, 1)), obs=obs),
+        region=["s1"],
+        region_key="region",
+        instance_key="instance_id",
+    )
+    sdata = SpatialData(shapes={"s1": shapes}, tables={"t": table})
+
+    fig, ax = plt.subplots()
+    sdata.pl.render_shapes("s1", color="cat", table_name="t").pl.show(ax=ax)
+    assert sorted(t.get_text() for t in ax.get_legend().get_texts()) == ["A", "B"]
+    plt.close(fig)
+
+    fig, ax = plt.subplots()
+    sdata.pl.render_shapes("s1", color="cat").pl.show(ax=ax)
+    assert sorted(t.get_text() for t in ax.get_legend().get_texts()) == ["X", "Y"]
+    plt.close(fig)