diff --git a/nodes.py b/nodes.py
index a6081cb..d477846 100644
--- a/nodes.py
+++ b/nodes.py
@@ -2400,10 +2400,11 @@ class WanVideoSampler:
             
             random_ref_dwpose_data = None
             if image_cond is not None:
-                random_ref_dwpose = unianimate_poses["ref"]
-                random_ref_dwpose_data = transformer.randomref_embedding_pose(
-                    random_ref_dwpose.to(device)#.permute(0,3,1,2)
-                    ).unsqueeze(2).to(model["dtype"]) # [1, 20, 104, 60]
+                random_ref_dwpose = unianimate_poses.get("ref", None)
+                if random_ref_dwpose is not None:
+                    random_ref_dwpose_data = transformer.randomref_embedding_pose(
+                        random_ref_dwpose.to(device)
+                        ).unsqueeze(2).to(model["dtype"]) # [1, 20, 104, 60]
                 
             unianim_data = {
                 "dwpose": dwpose_data,
diff --git a/unianimate/nodes.py b/unianimate/nodes.py
index a656956..be1e2ff 100644
--- a/unianimate/nodes.py
+++ b/unianimate/nodes.py
@@ -763,11 +763,13 @@ class WanVideoUniAnimatePoseInput:
     def INPUT_TYPES(s):
         return {"required": {
             "pose_images": ("IMAGE", {"tooltip": "Pose images"}),
-            "reference_pose_image": ("IMAGE", {"tooltip": "Reference pose image"}),
             "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Strength of the pose control"}),
             "start_percent": ("FLOAT", {"default": 0.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "Start percentage for the pose control"}),
             "end_percent": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01, "tooltip": "End percentage for the pose control"}),
             },
+            "optional": {
+                "reference_pose_image": ("IMAGE", {"tooltip": "Reference pose image"}),
+            },
         }
 
     RETURN_TYPES = ("UNIANIMATE_POSE", )
@@ -775,10 +777,13 @@ class WanVideoUniAnimatePoseInput:
     FUNCTION = "process"
     CATEGORY = "WanVideoWrapper"
 
-    def process(self, pose_images, reference_pose_image, strength, start_percent, end_percent):
+    def process(self, pose_images, strength, start_percent, end_percent, reference_pose_image=None):
 
         pose = pose_images.permute(3, 0, 1, 2).unsqueeze(0).contiguous()
-        ref = reference_pose_image.permute(0, 3, 1, 2).contiguous()
+
+        ref = None
+        if reference_pose_image is not None:
+            ref = reference_pose_image.permute(0, 3, 1, 2).contiguous()
 
         unianim_poses = {
             "pose": pose,
diff --git a/wanvideo/modules/model.py b/wanvideo/modules/model.py
index 40f68ed..ea032df 100644
--- a/wanvideo/modules/model.py
+++ b/wanvideo/modules/model.py
@@ -1001,7 +1001,8 @@ class WanModel(ModelMixin, ConfigMixin):
             if hasattr(self, "randomref_embedding_pose") and unianim_data is not None:
                 if unianim_data['start_percent'] <= current_step_percentage <= unianim_data['end_percent']:
                     random_ref_emb = unianim_data["random_ref"]
-                    y[0] = y[0] + random_ref_emb * unianim_data["strength"]
+                    if random_ref_emb is not None:
+                        y[0] = y[0] + random_ref_emb * unianim_data["strength"]
             x = [torch.cat([u, v], dim=0) for u, v in zip(x, y)]
 
         # embeddings