SparseCtrl-HOI: Sparse Temporal Control for Human-Object Interaction Video Generation
Official Implementation
This repo contains the PyTorch model definitions, pre-trained weights, and training/inference/evaluation code for our paper SparseCtrl-HOI: Sparse Temporal Control for Human-Object Interaction Video Generation (ECCV 2026).
SparseCtrl-HOI: Sparse Temporal Control for Human-Object Interaction Video Generation
Shenbo Xie, Mingrui Cai, Xu Yang, Yifei Liu, Changxing Ding*
(*Corresponding Author)
South China University of Technology
Videos generated by SparseCtrl-HOI. The inset in each video shows the sparse interaction keyframe and its designated timestamp. More results with audio are available on the project page.
Code, models, and data are released in stages. Boxes are checked as each stage lands.
| Stage | Contents | Status |
|---|---|---|
| 0 | Project page, paper | ☑ |
| 1 | Inference: environment, pre-trained weights, inference script, demo samples | ☐ |
| 2 | Data preprocessing pipeline | ☐ |
| 3 | Two-stage training code | ☐ |
| 4 | SparseHOI-5K dataset | ☐ |
| 5 | Evaluation protocol and ablation configs | ☐ |
If you find this work useful for your research, please consider citing it.
@article{xie2026sparsectrl,
title={SparseCtrl-HOI: Sparse Temporal Control for Human-Object Interaction Video Generation},
author={Xie, Shenbo and Cai, Mingrui and Yang, Xu and Liu, Yifei and Ding, Changxing},
journal={arXiv preprint arXiv:2607.05994},
year={2026}
}SparseCtrl-HOI has been greatly inspired by the following amazing works and teams: Wan2.1, OmniAvatar, DiffSynth-Studio, and Qwen2.5-VL, we thank all the contributors for open-sourcing.
The code and model weights are licensed under LICENSE.