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Running on Zero
Running on Zero
| title: Lip Forcing | |
| emoji: 🗣️ | |
| colorFrom: indigo | |
| colorTo: green | |
| sdk: gradio | |
| app_file: app.py | |
| pinned: false | |
| python_version: "3.10" | |
| short_description: Few-step autoregressive diffusion for real-time lip sync | |
| startup_duration_timeout: 60m | |
| # Lip Forcing | |
| Gradio demo for **Lip Forcing: Few-Step Autoregressive Diffusion for Real-time | |
| Lip Synchronization** (KAIST AI · AIPARK), running the released self-contained | |
| **14B student** checkpoint. | |
| Given a talking-head reference video and a driving audio clip, the model detects | |
| and aligns the face to 512×512, then regenerates the mouth region to match the | |
| audio using a causal 2-step autoregressive diffusion student, and composites the | |
| result back into the original frames. | |
| - Paper: https://arxiv.org/abs/2606.11180 | |
| - Project page: https://cvlab-kaist.github.io/LipForcing/ | |
| - Code: https://github.com/cvlab-kaist/LipForcing | |
| - Weights: https://huggingface.co/JinhyukJang/lipforcing | |
| This demo reproduces the official streaming inference pipeline | |
| (`scripts/inference/inference_streaming.py`) 1:1 on ZeroGPU. Driving audio is | |
| capped to the first few seconds per request to keep a single call within the GPU | |
| time budget. | |