5 citations · 14 across the 13 of their papers we have counts for
14 papers
UniDiffFusion: A Unified Diffusion Framework for Multi-Task and Degradation-Robust Image Fusion
Xingxin Xu, Siqi Zhao, Xin Li +3
General image fusion aims to integrate complementary information from multiple source images, but existing methods often rely on task-specific models and struggle to maintain robus…
RACO: Reliability-Aware Coarse-Goal Optimization for Inspection-Oriented UAV Vision-Language Navigation
Sen Wang, Yiming Sun, Jiaxuan He +1
UAV vision-language navigation (UAV-VLN) is commonly evaluated as goal reaching, but inspection-oriented deployment requires the agent to stop within a valid inspection region and…
DynCur-Geo: Dynamic Curiosity Reward Shaping for Multimodal Active Geo-Localization
Yiming Sun, Yang Zhang, Pengfei Zhu
Active geo-localization enables low-altitude UAVs to search for specified targets from limited local aerial observations, supporting time-sensitive applications such as search and…
Rethinking Air-Ground Collaboration: A Progressive Cross-Task Benchmark and Socialized Learning Framework
Zhoupeng Guo, Yunqi Zhu, Zhihe Fan +6
Air-ground collaborative perception is crucial for robust visual understanding in real-world dynamic environments. However, existing studies typically formulate collaboration as si…
Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline
Zekai Zhang, Qinghui Chen, Maomao Xiong +6
Large Visual Language Models (LVLMs) have achieved remarkable success in vision tasks. However, the significant differences between industrial and natural scenes make applying LVLM…
CtrlFuse: Mask-Prompt Guided Controllable Infrared and Visible Image Fusion
Yiming Sun, Yuan Ruan, Qinghua Hu +1
Infrared and visible image fusion generates all-weather perception-capable images by combining complementary modalities, enhancing environmental awareness for intelligent unmanned…
DIFF-MF: A Difference-Driven Channel-Spatial State Space Model for Multi-Modal Image Fusion
Yiming Sun, Zifan Ye, Qinghua Hu +1
Multi-modal image fusion aims to integrate complementary information from multiple source images to produce high-quality fused images with enriched content. Although existing appro…
SmartSight: Mitigating Hallucination in Video-LLMs Without Compromising Video Understanding via Temporal Attention Collapse
Yiming Sun, Mi Zhang, Feifei Li +2
Despite Video Large Language Models having rapidly advanced in recent years, perceptual hallucinations pose a substantial safety risk, which severely restricts their real-world app…
Rethinking Multi-Modal Object Detection from the Perspective of Mono-Modality Feature Learning
Tianyi Zhao, Boyang Liu, Yanglei Gao +3
Multi-Modal Object Detection (MMOD), due to its stronger adaptability to various complex environments, has been widely applied in various applications. Extensive research is dedica…
Dynamic Brightness Adaptation for Robust Multi-modal Image Fusion
Yiming Sun, Bing Cao, Pengfei Zhu +1
Infrared and visible image fusion aim to integrate modality strengths for visually enhanced, informative images. Visible imaging in real-world scenarios is susceptible to dynamic e…
Learning Multimodal Cues of Children's Uncertainty
Qi Cheng, Mert İnan, Rahma Mbarki +6
Understanding uncertainty plays a critical role in achieving common ground (Clark et al.,1983). This is especially important for multimodal AI systems that collaborate with users t…
Multi-modal Gated Mixture of Local-to-Global Experts for Dynamic Image Fusion
Yiming Sun, Bing Cao, Pengfei Zhu +1
Infrared and visible image fusion aims to integrate comprehensive information from multiple sources to achieve superior performances on various practical tasks, such as detection,…
Multi-Drone based Single Object Tracking with Agent Sharing Network
Pengfei Zhu, Jiayu Zheng, Dawei Du +3
Drone equipped with cameras can dynamically track the target in the air from a broader view compared with static cameras or moving sensors over the ground. However, it is still cha…
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning
Yiming Sun, Bing Cao, Pengfei Zhu +1
Drone-based vehicle detection aims at finding the vehicle locations and categories in an aerial image. It empowers smart city traffic management and disaster rescue. Researchers ha…