In AI video generation, faces usually get destroyed the moment complex motion (like liquid splashing) is introduced. The AI gets confused between the face texture and the fluid texture.
The WAN 2.2 Face Cream Workflow solves this by integrating a dedicated Face Restoration Pipeline directly into the generation loop. It is designed specifically for close-up shots where preserving the model's identity is just as important as the action itself.
🛠 The Technical Breakdown
Looking at the node graph, this workflow is optimized for macro details. It doesn't try to do full-body movement; it focuses entirely on the face and the interaction with fluids.
The “f4c3cr34m” Engine: It utilizes a specialized LoRA
wan22-f4c3cr34m(Node 142). Unlike generic “cum” prompts, this LoRA is trained on the specific physics of liquid hitting and sliding down skin contours.Built-in Face Fixing: Node 166 triggers
ReActorRestoreFaceusing theGFPGANv1.4.pthmodel. This runs after the generation but before the upscale, ensuring that even if the Wan model distorts the eyes during the splash, the final video snaps them back to perfection.Auto-Upscaling: It includes an
ImageUpscaleWithModelnode (Node 103) utilizingRealESRGAN_x2. This means you can render at a lower resolution (saving speed) and let the workflow crispen the final output automatically.
⚡ Workflow Specs
Base Checkpoint:
wan2.2_i2v_high_noise_14BSampler:
lcm(beta)Steps: 6 (Optimized for speed)
Key LoRAs:
wan22-f4c3cr34m(The secret sauce),Wan21_I2V_14B_lightx2vExtras: Integrated
GFPGANFace Restore +RealESRGANUpscaler
🔗 Related Finish Workflows
WAN 2.2 Cumshot Workflow – full-body cumshot sequences with thick fluid physics.
WAN 2.2 Mouthfull Workflow – oral creampies with volumetric mouth mechanics.
WAN 2.2 Blowjob & Deepthroat Workflow – lead-up oral action before the finish.
Browse all WAN 2.2 workflows – explore the complete collection.
📝 How to Use This Workflow
Input: Load a close-up portrait image. The AI works best if the mouth is slightly open or the expression is expectant.
Trigger Word: Ensure
f4c3cr34mis at the start of your prompt. This triggers the specific physics model trained in the LoRA.Adjust Fidelity: If the face looks too perfect (plastic), lower the
codeformer_weightin the ReActor node (Node 166). If it looks distorted, increase it to 0.7 or 0.8.
👉 Get the WAN 2.2 Workflow Bundle
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🚀 Create This Exact Content
Want to replicate these results? You can download the exact Wan 2.2 Workflows used in this article, or skip the technical setup and generate videos instantly in our cloud studio.
