5 citations · 14 across the 13 of their papers we have counts for
7 papers · 1 filter
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…