UFM: A Simple Path towards Unified Dense Correspondence with Flow
Carnegie Mellon University
Yuchen Zhang, Nikhil Keetha, Chenwei Lyu, Bhuvan Jhamb, Yutian Chen Yuheng Qiu, Jay Karhade, Shreyas Jha, Yaoyu Hu Deva Ramanan, Sebastian Scherer, Wenshan Wang
Overview
UFM(UniFlowMatch) is a simple, end-to-end trained transformer model that directly regresses pixel displacement image that applies concurrently to both optical flow and wide-baseline matching tasks.
This model space contains the refine model.
Quick Start
Check out our Github Repo and the hugging face demo.
Citation
If you find our repository useful, please consider giving it a star โญ and citing our paper in your work:
@inproceedings{zhang2025ufm,
title={UFM: A Simple Path towards Unified Dense Correspondence with Flow},
author={Zhang, Yuchen and Keetha, Nikhil and Lyu, Chenwei and Jhamb, Bhuvan and Chen, Yutian and Qiu, Yuheng and Karhade, Jay and Jha, Shreyas and Hu, Yaoyu and Ramanan, Deva and Scherer, Sebastian and Wang, Wenshan},
booktitle={arXiV},
year={2025}
}
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