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
@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}
}