Research map / Image generation / Editing and style transfer
StableAnimator: High-Quality Identity-Preserving Human Image Animation
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Proposes StableAnimator, an end-to-end ID-preserving video diffusion framework for pose-driven human image animation, using a global content-aware Face Encoder, a distribution-aware ID Adapter, and HJB-equation-based face optimization at inference.
Problem
Pose-driven human image animation with diffusion models suffers from identity inconsistency and facial distortion, and existing fixes rely on post-processing face-swapping tools that degrade video quality.
Approach
Injects ID information into a video diffusion U-Net via a Face Encoder that attends to reference image embeddings and an ID Adapter that aligns face-attention features to image-attention feature statistics (mean/std) before temporal layers; additionally, an HJB-equation-based optimization of the predicted sample toward ArcFace similarity is interleaved with EDM denoising at inference.
Key results
- StableAnimator reaches CSIM 0.831 on TikTok and FVD 140.62, the best among compared methods, and outperforms ControlNeXt by 47.1% in CSIM.
- On Unseen100, StableAnimator outperforms Unianimate by 45.8% in CSIM (0.805 vs 0.347 for Unianimate as reported in Table 1 setting).
- User study on 30 videos shows users prefer StableAnimator over all competitors for motion, appearance, background, and ID alignment in most cases (e.g., 95.6% vs DisCo for motion).
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use StableAnimator instead of Unianimate | human image animation · TikTok | CSIM: 0.479 -> 0.831 | Helped |
| Use StableAnimator instead of Unianimate | human image animation · TikTok | FVD: 148.06 -> 140.62 | Helped |
| Use StableAnimator instead of Unianimate | human image animation · Unseen100 | CSIM: 0.347 -> 0.805 | Helped |
| Use StableAnimator instead of ControlNeXt | human image animation · Unseen100 | FVD: 389.45 -> 349.94 | Helped |
| add face masks to the loss (ablation) | StableAnimator · Unseen100 | CSIM: 0.639 -> 0.805 | Helped |
| add the Face Encoder (ablation) | StableAnimator · Unseen100 | CSIM: 0.594 -> 0.805 | Helped |
| add distribution alignment to the ID Adapter (ablation) | StableAnimator · Unseen100 | FVD: 412.52 -> 349.94 | Helped |
| add HJB-based face optimization (ablation) | StableAnimator · Unseen100 | CSIM: 0.782 -> 0.805 | Helped |
| replace the proposed face strategy with IP-Adapter (ablation) | StableAnimator · Unseen100 | FVD: 349.94 -> 484.77 | Hurt |
| replace the proposed face strategy with FaceFusion (ablation) | StableAnimator · Unseen100 | CSIM: 0.805 -> 0.798 | No clear effect |
| replace distribution alignment with element-wise addition (ablation) | StableAnimator · Unseen100 | FVD: 349.94 -> 412.52 | Hurt |
| replace distribution alignment with normalization (ablation) | StableAnimator · Unseen100 | FVD: 349.94 -> 382.49 | Hurt |
Surprising findings
- Adding IP-Adapter for ID injection improves CSIM but substantially degrades video fidelity (FVD rises from 371.38 to 484.77 in the ablation) and single-frame quality.
Limitations
- Training data (3K internet videos) is not released, limiting reproducibility.
- Face optimization adds inference-time cost via 10 Adam steps through the VAE decoder and ArcFace at each denoising step.
Experimental setup
Datasets: TikTok dataset Unseen100 self-collected 3K internet videos
Benchmarks: TikTok Unseen100
Metrics: L1 PSNR SSIM LPIPS CSIM FVD
Baselines: MRAA DisCo MagicAnimate AnimateAnyone Champ Unianimate MimicMotion ControlNeXt
Builds on: Stable Video Diffusion AnimateAnyone EDM IP-Adapter
Closest papers by meaning
- MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model (CVPR 2024 · similarity 0.88)
- FaithfulFaces: Pose-Faithful Facial Identity Preservation for Text-to-Video Generation (NeurIPS 2026 · similarity 0.88)
- When StyleGAN Meets Stable Diffusion: a W+ Adapter for Personalized Image Generation (CVPR 2024 · similarity 0.88)
- $\text{ID}^3$: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition (NeurIPS 2024 · similarity 0.87)
- Identity-Preserving Text-to-Video Generation by Frequency Decomposition (CVPR 2025 · similarity 0.86)
- EverAnimate: Minute-Scale Human Animation via Latent Flow Restoration (NeurIPS 2026 · similarity 0.86)
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