Motion324 / README.md
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---
license: cc-by-nc-sa-4.0
pipeline_tag: image-to-3d
---
# Motion 3-to-4: 3D Motion Reconstruction for 4D Synthesis
**Motion 3-to-4** reconstructs 3D motion from video inputs for 4D synthesis, enabling the generation of animated 3D models with realistic motion in a feed-forward manner.
[Paper](https://arxiv.org/abs/2601.14253) | [Project Page](https://motion3-to-4.github.io/) | [Code](https://github.com/Inception3D/Motion324)
## Abstract
Motion 3-to-4 is a feed-forward framework for synthesising high-quality 4D dynamic objects from a single monocular video and an optional 3D reference mesh. It addresses challenges in 4D synthesis by decomposing the task into static 3D shape generation and motion reconstruction. Using a canonical reference mesh, the model learns a compact motion latent representation and predicts per-frame vertex trajectories to recover complete, temporally coherent geometry. A scalable frame-wise transformer further enables robustness to varying sequence lengths.
## Quick Start
### Installation
```bash
git clone https://github.com/Inception3D/Motion324.git
cd Motion324
conda create -n Motion324 python=3.11
conda activate Motion324
pip install -r requirements.txt
# (Optional) Install Hunyuan3D-2.0 modules
cd scripts/hy3dgen/texgen/custom_rasterizer && python3 setup.py install && cd ../../../..
cd scripts/hy3dgen/texgen/differentiable_renderer && python3 setup.py install && cd ../../../..
```
### Inference
Download the pre-trained checkpoints and place them in `experiments/checkpoints/`.
**Reconstruct 4D from an existing mesh and video:**
```bash
chmod +x ./scripts/4D_from_existing.sh
./scripts/4D_from_existing.sh ./examples/chili.glb ./examples/chili.mp4 ./examples/output
```
**Generate 4D animation from a single video input (requires Hunyuan):**
```bash
chmod +x ./scripts/4D_from_video.sh
./scripts/4D_from_video.sh ./examples/tiger.mp4
```
## Citation
If you find this work useful, please cite:
```bibtex
@article{chen2026motion3to4,
title={Motion 3-to-4: 3D Motion Reconstruction for 4D Synthesis},
author={Hongyuan, Chen and Xingyu, Chen and Youjia Zhang, and Zexiang, Xu and Anpei, Chen},
journal={arXiv preprint arXiv:2601.14253},
year={2026}
}
```