diff --git a/modules/impact/core.py b/modules/impact/core.py
index 32b350c5..6ff4a184 100644
--- a/modules/impact/core.py
+++ b/modules/impact/core.py
@@ -420,38 +420,11 @@ def enhance_detail_for_animatediff(image_frames, model, clip, vae, guide_size, g
     # upscale the mask tensor by a factor of 2 using bilinear interpolation
     if isinstance(noise_mask, np.ndarray):
         noise_mask = torch.from_numpy(noise_mask)
+    noise_mask = noise_mask.unsqueeze(0) if len(noise_mask.shape) == 2 else noise_mask
+    upscaled_mask = [torch.nn.functional.interpolate(m.unsqueeze(0).unsqueeze(0), size=(new_h, new_w), mode='bilinear', align_corners=False).squeeze(0) for m in noise_mask]
+    upscaled_mask = torch.stack(upscaled_mask, dim=0) if len(upscaled_mask) > 1 else upscaled_mask[0]
 
-    if len(noise_mask.shape) == 2:
-        noise_mask = noise_mask.unsqueeze(0)
-    else:  # == 3
-        noise_mask = noise_mask
-
-    upscaled_mask = None
-
-    for single_mask in noise_mask:
-        single_mask = single_mask.unsqueeze(0).unsqueeze(0)
-        upscaled_single_mask = torch.nn.functional.interpolate(single_mask, size=(new_h, new_w), mode='bilinear', align_corners=False)
-        upscaled_single_mask = upscaled_single_mask.squeeze(0)
-
-        if upscaled_mask is None:
-            upscaled_mask = upscaled_single_mask
-        else:
-            upscaled_mask = torch.cat((upscaled_mask, upscaled_single_mask), dim=0)
-
-    latent_frames = None
-    for image in image_frames:
-        image = torch.from_numpy(image).unsqueeze(0)
-
-        # upscale
-        upscaled_image = tensor_resize(image, new_w, new_h)
-
-        # ksampler
-        samples = to_latent_image(upscaled_image, vae)['samples']
-
-        if latent_frames is None:
-            latent_frames = samples
-        else:
-            latent_frames = torch.concat((latent_frames, samples), dim=0)
+    latent_frames = torch.cat([to_latent_image(tensor_resize(torch.from_numpy(frame).unsqueeze(0), new_w, new_h)['samples']) for frame in image_frames], dim=0)
 
     cnet_images = None
     if control_net_wrapper is not None: