@inproceedings{Liu_2025_CVPR,author={Liu, Shanglin and Lv, Jianming and Kang, Jingdan and Zhang, Huaidong and Liang, Zequan and He, Shengfeng},title={MODfinity: Unsupervised Domain Adaptation with Multimodal Information Flow Intertwining},booktitle={Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR)},month=jun,year={2025},pages={5092-5101},}
FS-Diff: Semantic guidance and clarity-aware simultaneous multimodal image fusion and super-resolution
Yuchan Jie, Yushen Xu, Xiaosong Li, and 3 more authors
@inproceedings{Differentiated2021,author={Lv, Jianming and Liu, Kaijie and He, Shengfeng},title={Differentiated Learning for Multi-Modal Domain Adaptation},year={2021},isbn={9781450386517},publisher={Association for Computing Machinery},address={New York, NY, USA},url={https://doi.org/10.1145/3474085.3475660},doi={10.1145/3474085.3475660},booktitle={Proceedings of the 29th ACM International Conference on Multimedia},pages={1322–1330},numpages={9},keywords={multi-modal analysis, domain adaptation, differentiated learning},series={MM '21},}
@article{chen2021adversarial,title={Adversarial caching training: Unsupervised inductive network representation learning on large-scale graphs},author={Chen, Junyang and Gong, Zhiguo and Wang, Wei and Wang, Cong and Xu, Zhenghua and Lv, Jianming and Li, Xueliang and Wu, Kaishun and Liu, Weiwen},journal={IEEE Transactions on Neural Networks and Learning Systems},volume={33},number={12},pages={7079--7090},year={2021},publisher={IEEE},}