5 citations · 14 across the 20 of their papers we have counts for
8 papers · 1 filter
Multimodal Negative Learning
Baoquan Gong, Xiyuan Gao, Pengfei Zhu +2
Multimodal learning systems often encounter challenges related to modality imbalance, where a dominant modality may overshadow others, thereby hindering the learning of weak modali…
Large Model Driven Solar Activity AI Forecaster: A Scalable Dual Data-Model Framework
Jingjing Wang, Pengyu Liang, Tingyu Wang +12
Solar activity drives space weather, affecting Earth's magnetosphere and technological infrastructure, which makes accurate solar flare forecasting critical. Current space weather…
Generalized Few-Shot Out-of-Distribution Detection
Pinxuan Li, Bing Cao, Changqing Zhang +1
Few-shot Out-of-Distribution (OOD) detection has emerged as a critical research direction in machine learning for practical deployment. Most existing Few-shot OOD detection methods…
Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion
Timing Li, Bing Cao, Jiahe Feng +3
Image fusion synthesizes complementary information from multiple sources, mitigating the inherent limitations of unimodal imaging systems. Accurate image registration is essential…
Bi-directional Self-Registration for Misaligned Infrared-Visible Image Fusion
Timing Li, Bing Cao, Pengfei Zhu +2
Acquiring accurately aligned multi-modal image pairs is fundamental for achieving high-quality multi-modal image fusion. To address the lack of ground truth in current multi-modal…
Dig2DIG: Dig into Diffusion Information Gains for Image Fusion
Bing Cao, Baoshuo Cai, Changqing Zhang +1
Image fusion integrates complementary information from multi-source images to generate more informative results. Recently, the diffusion model, which demonstrates unprecedented gen…
Dream-IF: Dynamic Relative EnhAnceMent for Image Fusion
Xingxin Xu, Bing Cao, Dongdong Li +2
Image fusion aims to integrate comprehensive information from images acquired through multiple sources. However, images captured by diverse sensors often encounter various degradat…
Asymmetric Reinforcing against Multi-modal Representation Bias
Xiyuan Gao, Bing Cao, Pengfei Zhu +2
The strength of multimodal learning lies in its ability to integrate information from various sources, providing rich and comprehensive insights. However, in real-world scenarios,…