4 citations · 5 across the 3 of their papers we have counts for
4 papers
Toward Active Object Detection for UAVs in the Wild: A Large-Scale Dataset, Benchmark and Method
Tianpeng Liu, Xinhua Jiang, Li Liu +4
Object detection is a fundamental component in numerous Unmanned Aerial Vehicle (UAV) applications, yet it has long been plagued by hindrances like occlusion or target pixel scarci…
Fusion Meets Diverse Conditions: A High-diversity Benchmark and Baseline for UAV-based Multimodal Object Detection with Condition Cues
Chen Chen, Kangcheng Bin, Ting Hu +6
Unmanned aerial vehicles (UAV)-based object detection with visible (RGB) and infrared (IR) images facilitates robust around-the-clock detection, driven by advancements in deep lear…
Uncovering Bias in Foundation Models: Impact, Testing, Harm, and Mitigation
Shuzhou Sun, Li Liu, Yongxiang Liu +4
Bias in Foundation Models (FMs) - trained on vast datasets spanning societal and historical knowledge - poses significant challenges for fairness and equity across fields such as h…
A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution
Zhixiong Yang, Jingyuan Xia, Shengxi Li +5
Deep learning-based methods have achieved significant successes on solving the blind super-resolution (BSR) problem. However, most of them request supervised pre-training on labell…