15 citations · 35 across the 35 of their papers we have counts for
7 papers · 1 filter
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…
Dynamic Subframe Splitting and Spatio-Temporal Motion Entangled Sparse Attention for RGB-E Tracking
Pengcheng Shao, Tianyang Xu, Xuefeng Zhu +2
Event-based bionic camera asynchronously captures dynamic scenes with high temporal resolution and high dynamic range, offering potential for the integration of events and RGB unde…
MMDRFuse: Distilled Mini-Model with Dynamic Refresh for Multi-Modality Image Fusion
Yanglin Deng, Tianyang Xu, Chunyang Cheng +2
In recent years, Multi-Modality Image Fusion (MMIF) has been applied to many fields, which has attracted many scholars to endeavour to improve the fusion performance. However, the…
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action Recognition
Rongchang Li, Zhenhua Feng, Tianyang Xu +5
Compositional actions consist of dynamic (verbs) and static (objects) concepts. Humans can easily recognize unseen compositions using the learned concepts. For machines, solving su…
TENet: Targetness Entanglement Incorporating with Multi-Scale Pooling and Mutually-Guided Fusion for RGB-E Object Tracking
Pengcheng Shao, Tianyang Xu, Zhangyong Tang +3
There is currently strong interest in improving visual object tracking by augmenting the RGB modality with the output of a visual event camera that is particularly informative abou…
Revisiting RGBT Tracking Benchmarks from the Perspective of Modality Validity: A New Benchmark, Problem, and Solution
Zhangyong Tang, Tianyang Xu, Zhenhua Feng +4
RGBT tracking draws increasing attention because its robustness in multi-modal warranting (MMW) scenarios, such as nighttime and adverse weather conditions, where relying on a sing…
An Improved Graph Pooling Network for Skeleton-Based Action Recognition
Cong Wu, Xiao-Jun Wu, Tianyang Xu +1
Pooling is a crucial operation in computer vision, yet the unique structure of skeletons hinders the application of existing pooling strategies to skeleton graph modelling. In this…