---
library_name: pytorch
pipeline_tag: other
license: apache-2.0
tags:
  - computer-vision
  - autonomous-driving
  - world-model
  - future-prediction
  - depth-estimation
  - image-to-image
  - 4d-scene-understanding
  - nuscenes
  - unifuture
---

# UniFuture

**UniFuture: A 4D Driving World Model for Future Generation and Perception**

Official Hugging Face repository for **UniFuture**.

## Model description

UniFuture is a driving world model that jointly models future scene **appearance** and **geometry** within a unified framework.  
Given the current image as input, it predicts future **RGB-depth pairs** for future generation and perception.

According to the project description, UniFuture introduces:

- **Dual-Latent Sharing** for shared latent learning between image and depth sequences
- **Multi-scale Latent Interaction** for bidirectional refinement between image and depth features across spatial scales

## Paper

**UniFuture: A 4D Driving World Model for Future Generation and Perception**  
ICRA 2026

## Repository contents

- `unifuture.safetensors`: pretrained model weights

## Task

This repository is intended for research use on **driving world modeling**, including:

- future scene generation
- future depth prediction
- future perception

## Dataset

The paper reports experiments on **nuScenes**.

## Usage

Please refer to the official GitHub repository for training, evaluation, and detailed usage instructions:

`https://github.com/dk-liang/UniFuture`

## License

Apache-2.0

## Citation

```bibtex
@inproceedings{liang2026UniFuture,
  title={UniFuture: A 4D Driving World Model for Future Generation and Perception},
  author={Liang, Dingkang and Zhang, Dingyuan and Zhou, Xin and Tu, Sifan and Feng, Tianrui and Li, Xiaofan and Zhang, Yumeng and Du, Mingyang and Tan, Xiao and Bai, Xiang},
  booktitle={IEEE International Conference on Robotics and Automation},
  year={2026}
}