5 papers
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…
Deep Learning Reforms Image Matching: A Survey and Outlook
Shihua Zhang, Zizhuo Li, Kaining Zhang +5
Image matching, which establishes correspondences between two-view images to recover 3D structure and camera geometry, serves as a cornerstone in computer vision and underpins a wi…
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…
DSPFusion: Image Fusion via Degradation and Semantic Dual-Prior Guidance
Linfeng Tang, Chunyu Li, Guoqing Wang +2
Existing fusion methods are tailored for high-quality images but struggle with degraded images captured under harsh circumstances, thus limiting the practical potential of image fu…
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…