15 citations · 16 across the 9 of their papers we have counts for
9 papers
Partial Skeleton Visibility for Action Recognition: A Constrained Field-of-View Approach
Yingjie Dai, Tianyang Xu, Yanglin Deng +2
Skeleton-based action recognition has achieved remarkable success by exploiting joint coordinates and their topological connections, yet prevailing methods overwhelmingly assume co…
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…
Learning Structure-Supporting Dependencies via Keypoint Interactive Transformer for General Mammal Pose Estimation
Tianyang Xu, Jiyong Rao, Xiaoning Song +2
General mammal pose estimation is an important and challenging task in computer vision, which is essential for understanding mammal behaviour in real-world applications. However, e…
UASTrack: A Unified Adaptive Selection Framework with Modality-Customization in Single Object Tracking
He Wang, Tianyang Xu, Zhangyong Tang +2
Multi-modal tracking is essential in single-object tracking (SOT), as different sensor types contribute unique capabilities to overcome challenges caused by variations in object ap…
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…
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…