38 citations · 95 across the 44 of their papers we have counts for
12 papers · 1 filter
Comprehensive, Efficient Large-Scale Community Detection via Structural Entropy Game
Pu Li, Yantuan Xian, Hao Peng +4
Community detection is a critical task in graph theory, social network analysis, and bioinformatics, where communities are defined as clusters of densely interconnected nodes. Howe…
Multi-modality Image Fusion under Adverse Weather: Mask-Guided Feature Restoration and Interaction
Xilai Li, Xiaosong Li, Haishu Tan +3
Multi-modality image fusion (MMIF) enhances scene representation by exploiting complementary cues from different modalities. Adverse weather, however, causes significant image degr…
One Stone, Three Birds: Self-adaptive Optimal Transport for Multi-VLM Selection, Adaptation, and Ensembling
Qiyu Xu, Zhanxuan Hu, Yu Duan +4
Vision-language models (VLMs) enable visual recognition from semantic class descriptions, which makes them attractive when target annotations are scarce or unavailable. Most deploy…
Geometry-Preserving Unsupervised Alignment for Heterogeneous Foundation Models
Shuwen Yu, Zhanxuan Hu, Yi Zhao +2
Foundation models have driven rapid progress in computer vision, yet the two dominant paradigms, vision-language foundation models (VLMs) and vision-only foundation models (VFMs),…
[CLS] is Not Enough: Multi-Label Recognition via Patch-Level Inference and Adaptive Aggregation
Akang Wang, Xili Deng, Zhanxuan Hu +3
Vision-Language Models such as CLIP exhibit strong zero-shot recognition capability by aligning images with textual concepts, yet they often underperform on multi-label recognition…
Expandable, Compressible, Mineable: Open-World Thermal Image Restoration
Pu Li, Huafeng Li, Yafei Zhang +3
In open-world settings, thermal infrared (TIR) image degradations continuously emerge and evolve, while most existing all-in-one restoration methods are built on a closed-set assum…
Breaking Degradation Coupling: A Structural Entropy Guided Decoupled Framework and Benchmark for Infrared Enhancement
Pu Li, Huafeng Li, Yafei Zhang +2
Thermal infrared image enhancement aims to restore high-quality images from complex compound degradations. Existing all-in-one approaches typically employ a single shared backbone…
Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusion
Zengyi Yang, Yu Liu, Juan Cheng +3
Infrared-visible image fusion aims to integrate complementary information for robust visual understanding, but existing fusion methods struggle with simultaneously adapting to mult…
Degradation-Robust Fusion: An Efficient Degradation-Aware Diffusion Framework for Multimodal Image Fusion in Arbitrary Degradation Scenarios
Yu Shi, Yu Liu, Zhong-Cheng Wu +3
Complex degradations like noise, blur, and low resolution are typical challenges in real world image fusion tasks, limiting the performance and practicality of existing methods. En…
MAVFusion: Efficient Infrared and Visible Video Fusion via Motion-Aware Sparse Interaction
Xilai Li, Weijun Jiang, Xiaosong Li +5
Infrared and visible video fusion combines the object saliency from infrared images with the texture details from visible images to produce semantically rich fusion results. Howeve…
Missing No More: Dictionary-Guided Cross-Modal Image Fusion under Missing Infrared
Yafei Zhang, Meng Ma, Huafeng Li +1
Infrared-visible (IR-VIS) image fusion is vital for perception and security, yet most methods rely on the availability of both modalities during training and inference. When the in…
Adaptive Dynamic Dehazing via Instruction-Driven and Task-Feedback Closed-Loop Optimization for Diverse Downstream Task Adaptation
Yafei Zhang, Shuaitian Song, Huafeng Li +2
In real-world vision systems,haze removal is required not only to enhance image visibility but also to meet the specific needs of diverse downstream tasks.To address this challenge…