13 citations · 36 across the 14 of their papers we have counts for
14 papers
ReflexTrack: A Feedback-Driven Agent for Training-Free Referring Video Object Segmentation
Yuanjia Li, Tianyang Xu, Tao Zhou +3
Referring video object segmentation (RVOS) requires segmenting a target specified by natural language throughout a video. Recent agentic approaches combine multimodal large languag…
EvaNet: Towards More Efficient and Consistent Infrared and Visible Image Fusion Assessment
Chunyang Cheng, Tianyang Xu, Xiao-Jun Wu +4
Evaluation is essential in image fusion research, yet most existing metrics are directly borrowed from other vision tasks without proper adaptation. These traditional metrics, ofte…
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…
Omni Survey for Multimodality Analysis in Visual Object Tracking
Zhangyong Tang, Tianyang Xu, Xuefeng Zhu +6
The development of smart cities has led to the generation of massive amounts of multi-modal data in the context of a range of tasks that enable a comprehensive monitoring of the sm…
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…
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…
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…
TextFusion: Unveiling the Power of Textual Semantics for Controllable Image Fusion
Chunyang Cheng, Tianyang Xu, Xiao-Jun Wu +4
Advanced image fusion methods are devoted to generating the fusion results by aggregating the complementary information conveyed by the source images. However, the difference in th…
Generative-based Fusion Mechanism for Multi-Modal Tracking
Zhangyong Tang, Tianyang Xu, Xuefeng Zhu +2
Generative models (GMs) have received increasing research interest for their remarkable capacity to achieve comprehensive understanding. However, their potential application in the…
RGBD1K: A Large-scale Dataset and Benchmark for RGB-D Object Tracking
Xue-Feng Zhu, Tianyang Xu, Zhangyong Tang +5
RGB-D object tracking has attracted considerable attention recently, achieving promising performance thanks to the symbiosis between visual and depth channels. However, given a lim…
A Survey for Deep RGBT Tracking
Zhangyong Tang, Tianyang Xu, Xiao-Jun Wu
Visual object tracking with the visible (RGB) and thermal infrared (TIR) electromagnetic waves, shorted in RGBT tracking, recently draws increasing attention in the tracking commun…
Temporal Aggregation for Adaptive RGBT Tracking
Zhangyong Tang, Tianyang Xu, Xiao-Jun Wu
Visual object tracking with RGB and thermal infrared (TIR) spectra available, shorted in RGBT tracking, is a novel and challenging research topic which draws increasing attention n…
Exploring Fusion Strategies for Accurate RGBT Visual Object Tracking
Zhangyong Tang, Tianyang Xu, Hui Li +3
We address the problem of multi-modal object tracking in video and explore various options of fusing the complementary information conveyed by the visible (RGB) and thermal infrare…