most citedProvable Dynamic Fusion for Low-Quality Multimodal Data

20 citations · 23 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG2024

Multimodal Fusion on Low-quality Data: A Comprehensive Survey

Qingyang Zhang, Yake Wei, Zongbo Han +8

Multimodal fusion focuses on integrating information from multiple modalities with the goal of more accurate prediction, which has achieved remarkable progress in a wide range of s…

cs.LG202320 cited

Provable Dynamic Fusion for Low-Quality Multimodal Data

Qingyang Zhang, Haitao Wu, Changqing Zhang +4

The inherent challenge of multimodal fusion is to precisely capture the cross-modal correlation and flexibly conduct cross-modal interaction. To fully release the value of each mod…

cs.CV20231 cited

dugMatting: Decomposed-Uncertainty-Guided Matting

Jiawei Wu, Changqing Zhang, Zuoyong Li +3

Cutting out an object and estimating its opacity mask, known as image matting, is a key task in image and video editing. Due to the highly ill-posed issue, additional inputs, typic…

cs.CV2023

Semantic Invariant Multi-view Clustering with Fully Incomplete Information

Pengxin Zeng, Mouxing Yang, Yiding Lu +3

Robust multi-view learning with incomplete information has received significant attention due to issues such as incomplete correspondences and incomplete instances that commonly af…

cs.LG20232 cited

Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification

Mengyao Xie, Zongbo Han, Changqing Zhang +2

Classifying incomplete multi-view data is inevitable since arbitrary view missing widely exists in real-world applications. Although great progress has been achieved, existing inco…

cs.LG2023

Reweighted Mixup for Subpopulation Shift

Zongbo Han, Zhipeng Liang, Fan Yang +8

Subpopulation shift exists widely in many real-world applications, which refers to the training and test distributions that contain the same subpopulation groups but with different…