🕺 Tensor Pose Animation Pipeline
A Modular, Open-Source System for Pose-Driven Animation Across Games, Video, and AI Models
🚀 Project Summary
Tensor Pose Animation Pipeline is a community-driven initiative to build an open-source system for pose-conditioned animation. By using standardized 128-point whole-body pose tensors (body, hands, face), this pipeline enables creators to animate characters across mediums — game engines, AI video models, and film pipelines — with motion sequences derived from pose data.
We aim to unify motion capture, AI generation, and animation retargeting into a modular framework that empowers solo devs, indie studios, and researchers alike.
🎯 Goals and Motivation
- Democratize animation through reusable, portable motion sequences.
- Define a standard tensor format to represent motion (128 keypoints).
- Enable cross-platform animation in Unity, Unreal, Blender, and AI tools like WAN2.1 and ComfyUI.
- Support audio-driven choreography, style transfer, and live puppeteering.
- Invite collaboration across devs, ML researchers, animators, and toolmakers.
🧱 System Architecture Overview
The pipeline is composed of several modular layers:
Pose Capture/Import
- From videos (e.g., DWPose, OpenPose, DensePose)
- From motion libraries (e.g., AIST++, CMU Mocap)
- From live camera streams or VTuber setups
Core Pose Engine
- Normalizes all poses to a 128-point skeleton
- Applies style and timing adjustments
- Outputs retargetable motion tensor sequences
Integration Targets
- 🎮 Unity & Unreal Engine (via plugins or animation exports)
- 🎥 AI video models (e.g., WAN2.1 with ControlNet-style pose conditioning)
- 🛠️ Blender, After Effects, FBX/BVH/JSON export
Audio Synchronization
- Beat detection (e.g., Librosa, Madmom)
- Temporal alignment or retiming of pose sequences
- Music-to-motion synthesis options
Style Transfer (WIP)
- Modify motion tone (e.g., "graceful", "robotic")
- Transfer poses between rigs or visual archetypes
- Planned: Transformers or motion-style VAEs
Real-Time Preview Mode (future goal)
- Lightweight pipeline mode for streaming poses to Unity/Blender
- Potential for real-time webcam-to-avatar choreography
⚙️ Technical Challenges & Solutions
| Challenge | Proposed Solution |
|---|---|
| 🧩 Format Interoperability | Define 128pt spec + adapters for OpenPose, BVH, SMPL |
| 🤖 Motion Realism | Temporal smoothing, foot locking, inverse kinematics |
| 🎵 Audio Sync Precision | Multi-method BPM detection + beat-aligned retiming |
| 🔄 Game Engine Integration | Export to FBX/BVH + real-time plugins (Unity/Unreal) |
| 🧬 Identity Consistency | Style-preserving character LoRAs + ControlNet tuning |
| 🧠 Scalability & Compute | Batch processing, caching, Colab/Spaces integration |
🛠️ Implementation Plan
Phase 1: MVP – Pose to Video
- Define pose tensor schema
- Convert OpenPose/DWPose to tensor
- Basic JSON-to-Unity/FBX exporter
- WAN2.1 pose-to-video test with reference character
Phase 2: Expansion
- Unity and Unreal engine integrations
- Add support for AIST++ and BVH datasets
- Audio sync + basic retargeting tools
- Beat-aware motion remixer
Phase 3: Tooling & Style Transfer
- Implement motion filters (cartoonify, fluidify, etc.)
- Style transfer via transformers (MoStyle, etc.)
- Develop stable ControlNet-based workflows
Phase 4: Real-Time & Community
- Live pose streaming to Unity/VTuber setups
- Hugging Face Space demo (web-based animator)
- Contributor tutorials + dataset hub
- Start training or fine-tuning pose-to-video LoRA
🤝 Contribution Opportunities
- 🎮 Unity/Unreal plugin devs – Help build the real-time animation bridge
- 🧠 ML engineers – Optimize diffusion pipelines and pose-style transfer
- 📹 Creators – Use the pipeline, test with real projects, give feedback
- 📦 Dataset builders – Convert and contribute motion datasets (AIST++, Mixamo)
- 🧪 Researchers – Explore music-to-pose generation, realism metrics, or 3D interpolation
- 🔥 GPU donors – Share compute to fine-tune style LoRAs or ControlNet checkpoints
📣 Call to Action
We’re building the Tensor Pose Animation Pipeline as an open-source project for the community, by the community.
Help us by:
- ⭐ Starring the GitHub repo (coming soon)
- 🧵 Joining the discussions: ideas, issues, contributions
- 💻 Trying the demo (planned on Hugging Face Spaces)
- 🧠 Sharing research/code/models that improve the system
- 🚀 Helping indie creators bring characters to life through pose-driven AI
Together, we can make animation reusable, remixable, and radically accessible.
Built with inspiration from
🧠 VACE Dance Suite
🎶 AIST Dance DB
🎥 Wan2.1, AnimateDiff, ControlNet, DanceDiffusion, FACT
“One day, we’ll move characters the same way we move data — fluidly, semantically, and cross-platform.”
— Project LARP, 2025