diff --git a/python/tvm/relay/frontend/pytorch.py b/python/tvm/relay/frontend/pytorch.py
index 40b95d1d1f71..3cf0e080da67 100644
--- a/python/tvm/relay/frontend/pytorch.py
+++ b/python/tvm/relay/frontend/pytorch.py
@@ -1808,7 +1808,7 @@ def get_upsample_out_size(self, inputs, method):
                 else:
                     out_size.append(size)
         else:
-            scale_index = 3 if method == "linear" else 2
+            scale_index = 3 if method != "nearest_neighbor" else 2
             scales = inputs[scale_index]
             assert scales is not None, "neither out size nor scale provided"
             assert isinstance(scales, list)
@@ -1823,7 +1823,7 @@ def upsample(inputs, input_types):
             data = inputs[0]
             out_size = self.get_upsample_out_size(inputs, method)
 
-            if len(inputs) > 2 and method == "linear":
+            if len(inputs) > 2 and method != "nearest_neighbor":
                 align_corners = inputs[2]
             else:
                 align_corners = False
@@ -1836,7 +1836,9 @@ def upsample(inputs, input_types):
                 coord_trans = "half_pixel"
 
             def func(x):
-                return _op.image.resize2d(x, out_size, "NCHW", method, coord_trans)
+                return _op.image.resize2d(
+                    x, out_size, "NCHW", method, coord_trans, cubic_alpha=-0.75
+                )
 
             if self.is_quantized_tensor(data):
                 # input qparams are manually appended by us
@@ -2212,7 +2214,7 @@ def interpolate(self, inputs, input_types):
         else:
             coord_trans = "half_pixel"
 
-        return _op.image.resize2d(data, out_size, "NCHW", method, coord_trans)
+        return _op.image.resize2d(data, out_size, "NCHW", method, coord_trans, cubic_alpha=-0.75)
 
     def numel(self, inputs, input_types):
         return _op.ndarray_size(inputs[0])
@@ -2780,6 +2782,7 @@ def create_convert_map(self):
             "aten::clamp_": self.clamp,
             "aten::detach": self.identity,
             "aten::upsample_bilinear2d": self.make_upsample("linear"),
+            "aten::upsample_bicubic2d": self.make_upsample("cubic"),
             "aten::upsample_nearest2d": self.make_upsample("nearest_neighbor"),
             "aten::upsample_trilinear3d": self.make_upsample3d("linear"),
             "aten::upsample_nearest3d": self.make_upsample3d("nearest_neighbor"),
diff --git a/tests/python/frontend/pytorch/test_forward.py b/tests/python/frontend/pytorch/test_forward.py
index e58575266414..2e6828f693b6 100644
--- a/tests/python/frontend/pytorch/test_forward.py
+++ b/tests/python/frontend/pytorch/test_forward.py
@@ -1761,6 +1761,9 @@ def forward(self, x):
     verify_model(Upsample(size=(64, 64), mode="bilinear", align_corners=True), inp)
     verify_model(Upsample(scale=2, mode="bilinear", align_corners=True), inp)
     verify_model(Upsample(size=(50, 50), mode="bilinear", align_corners=True), inp)
+    verify_model(Upsample(size=(64, 64), mode="bicubic", align_corners=True), inp)
+    verify_model(Upsample(scale=2, mode="bicubic", align_corners=True), inp)
+    verify_model(Upsample(size=(50, 50), mode="bicubic", align_corners=True), inp)
 
 
 @tvm.testing.uses_gpu