7 papers
MagicFuse: Single Image Fusion for Visual and Semantic Reinforcement
Hao Zhang, Yanping Zha, Zizhuo Li +2
This paper focuses on a highly practical scenario: how to continue benefiting from the advantages of multi-modal image fusion under harsh conditions when only visible imaging senso…
VideoFusion: A Spatio-Temporal Collaborative Network for Multi-modal Video Fusion
Linfeng Tang, Yeda Wang, Meiqi Gong +7
Compared to images, videos better reflect real-world acquisition and possess valuable temporal cues. However, existing multi-sensor fusion research predominantly integrates complem…
ControlFusion: A Controllable Image Fusion Framework with Language-Vision Degradation Prompts
Linfeng Tang, Yeda Wang, Zhanchuan Cai +2
Current image fusion methods struggle to address the composite degradations encountered in real-world imaging scenarios and lack the flexibility to accommodate user-specific requir…
TemCoCo: Temporally Consistent Multi-modal Video Fusion with Visual-Semantic Collaboration
Meiqi Gong, Hao Zhang, Xunpeng Yi +2
Existing multi-modal fusion methods typically apply static frame-based image fusion techniques directly to video fusion tasks, neglecting inherent temporal dependencies and leading…
Robust Fusion Controller: Degradation-aware Image Fusion with Fine-grained Language Instructions
Hao Zhang, Yanping Zha, Qingwei Zhuang +2
Current image fusion methods struggle to adapt to real-world environments encompassing diverse degradations with spatially varying characteristics. To address this challenge, we pr…
CoMatch: Dynamic Covisibility-Aware Transformer for Bilateral Subpixel-Level Semi-Dense Image Matching
Zizhuo Li, Yifan Lu, Linfeng Tang +2
This prospective study proposes CoMatch, a novel semi-dense image matcher with dynamic covisibility awareness and bilateral subpixel accuracy. Firstly, observing that modeling cont…