15 citations · 35 across the 35 of their papers we have counts for
9 papers · 1 filter
SimWAM: A Simple World Action Model for End-to-End Autonomous Driving
Zongchuang Zhao, Xin Zhou, Tianyang Xu +6
In autonomous driving, World-Action Models (WAMs) have improved end-to-end planning by transferring video dynamics priors to action prediction, but many still couple planning with…
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…
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…
Text-Driven Fusion for Infrared and Visible Images: Achieving Image Scene Adaptation on Hyperbolic Space
Huan Kang, Hui Li, Tianyang Xu +3
Infrared and visible image fusion aims to integrate complementary modalities, while existing Euclidean methods impose rigid distance metrics that distort multi-modal interactions a…
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…
Beyond Strict Pairing: Arbitrarily Paired Training for High-Performance Infrared and Visible Image Fusion
Yanglin Deng, Tianyang Xu, Chunyang Cheng +3
Infrared and visible image fusion(IVIF) combines complementary modalities while preserving natural textures and salient thermal signatures. Existing solutions predominantly rely on…
Multi-Paradigm Collaborative Adversarial Attack Against Multi-Modal Large Language Models
Yuanbo Li, Tianyang Xu, Cong Hu +3
The rapid progress of Multi-Modal Large Language Models (MLLMs) has significantly advanced downstream applications. However, this progress also exposes serious transferable adversa…
Towards Highly Transferable Vision-Language Attack via Semantic-Augmented Dynamic Contrastive Interaction
Yuanbo Li, Tianyang Xu, Cong Hu +3
With the rapid advancement and widespread application of vision-language pre-training (VLP) models, their vulnerability to adversarial attacks has become a critical concern. In gen…
Learning Progressive Adaptation for Multi-Modal Tracking
He Wang, Tianyang Xu, Zhangyong Tang +2
Due to the limited availability of paired multi-modal data, multi-modal trackers are typically built by adopting pre-trained RGB models with parameter-efficient fine-tuning modules…