diff --git a/model-optimizer/extensions/middle/UpsampleToResample.py b/model-optimizer/extensions/middle/UpsampleToResample.py
index 0e34c1e2d319a2..e7e2a03f7344ba 100644
--- a/model-optimizer/extensions/middle/UpsampleToResample.py
+++ b/model-optimizer/extensions/middle/UpsampleToResample.py
@@ -79,15 +79,6 @@ def replace_pattern(self, graph: Graph, match: Dict[str, Node]):
             height_scale = upsample['height_scale']
             width_scale = upsample['width_scale']
 
-        if not math.isclose(height_scale, width_scale, rel_tol=1e-5):
-            log.debug('Width and height scales are not equal: {} vs {} for node {}'.format(
-                width_scale, height_scale, upsample_name))
-            return
-        if depth_scale is not None and not math.isclose(height_scale, depth_scale, rel_tol=1e-5):
-            log.debug('Depth and height scales are not equal: {} vs {} for node {}'.format(
-                depth_scale, height_scale, upsample_name))
-            return
-
         if 1 in upsample.in_ports() and not upsample.in_port(1).disconnected():
             upsample.in_port(1).disconnect()
 
diff --git a/model-optimizer/extensions/middle/UpsampleToResample_test.py b/model-optimizer/extensions/middle/UpsampleToResample_test.py
index d87a37fe039381..908d32d044b87d 100644
--- a/model-optimizer/extensions/middle/UpsampleToResample_test.py
+++ b/model-optimizer/extensions/middle/UpsampleToResample_test.py
@@ -100,7 +100,12 @@
 class UpsampleToResampleTest(unittest.TestCase):
     @generate(*[([2, 10, 20, 30], [1, 1, 5, 5],),
                 ([2, 20, 30, 40], [1, 1, 3, 3],),
-                ([2, 3, 20, 30, 40], [1, 1, 3, 3, 3],)
+                ([2, 10, 20, 30], [1, 1, 6, 5],),
+                ([2, 20, 30, 40], [1, 1, 3, 4],),
+                ([2, 3, 20, 30, 40], [1, 1, 3, 3, 3],),
+                ([2, 3, 20, 30, 40], [1, 1, 3, 4, 3],),
+                ([2, 3, 20, 30, 40], [1, 1, 4, 3, 3],),
+                ([2, 3, 20, 30, 40], [1, 1, 3, 3, 4],),
                 ])
     def test_conversion(self, input_shape, scales):
         graph = build_graph(graph_node_attrs, graph_edges,
@@ -122,11 +127,7 @@ def test_conversion(self, input_shape, scales):
         self.assertTrue(flag, resp)
 
     @generate(*[([2, 10, 20, 30], [1, 2, 5, 5],),
-                ([2, 10, 20, 30], [1, 1, 6, 5],),
-                ([2, 20, 30, 40], [1, 1, 3, 4],),
-                ([2, 3, 20, 30, 40], [1, 1, 3, 4, 3],),
-                ([2, 3, 20, 30, 40], [1, 1, 4, 3, 3],),
-                ([2, 3, 20, 30, 40], [1, 1, 3, 3, 4],),
+                ([2, 3, 20, 30, 40], [1, 2, 3, 3, 3],),
                 ])
     def test_pattern_does_not_satisfy(self, input_shape, scales):
         graph = build_graph(graph_node_attrs, graph_edges,
diff --git a/model-optimizer/extensions/ops/upsample.py b/model-optimizer/extensions/ops/upsample.py
index 613622c8b5a39d..dc2253ec28a4fb 100644
--- a/model-optimizer/extensions/ops/upsample.py
+++ b/model-optimizer/extensions/ops/upsample.py
@@ -63,5 +63,6 @@ def upsample_infer(node: Node):
                                                      width=out_width)
         else:
             assert node.in_node(1).value is not None
+            eps = 1e-5  # This is to make rounding in case of very close number to round to closest instead of down
             # generic output shape calculation to support 5D input shape case
-            node.out_node().shape = np.array(input_shape * node.in_node(1).value).astype(np.int64)
+            node.out_node().shape = np.array((input_shape + eps) * node.in_node(1).value).astype(np.int64)