5 papers
Serial Over Parallel: Learning Continual Unification for Multi-Modal Visual Object Tracking and Benchmarking
Zhangyong Tang, Tianyang Xu, Xuefeng Zhu +4
Unifying multiple multi-modal visual object tracking (MMVOT) tasks draws increasing attention due to the complementary nature of different modalities in building robust tracking sy…
GrFormer: A Novel Transformer on Grassmann Manifold for Infrared and Visible Image Fusion
Huan Kang, Hui Li, Xiao-Jun Wu +4
In the field of image fusion, promising progress has been made by modeling data from different modalities as linear subspaces. However, in practice, the source images are often loc…
One Model for ALL: Low-Level Task Interaction Is a Key to Task-Agnostic Image Fusion
Chunyang Cheng, Tianyang Xu, Zhenhua Feng +7
Advanced image fusion methods mostly prioritise high-level missions, where task interaction struggles with semantic gaps, requiring complex bridging mechanisms. In contrast, we pro…
One Latent Space to Rule All Degradations: Unifying Restoration Knowledge for Image Fusion
Haolong Ma, Hui Li, Chunyang Cheng +4
All-in-One Degradation-Aware Fusion Models (ADFMs) as one of multi-modal image fusion models, which aims to address complex scenes by mitigating degradations from source images and…
SMLNet: A SPD Manifold Learning Network for Infrared and Visible Image Fusion
Huan Kang, Hui Li, Tianyang Xu +4
Euclidean representation learning methods have achieved promising results in image fusion tasks, which can be attributed to their clear advantages in handling with linear space. Ho…