4 papers
Understand Before Detect: Vision--Language Learning for Omni-Domain Infrared Small Target Detection
Haoyang Yuan, Boyang Li, Yingqian Wang +7
Omni-domain infrared small target (IRST) detection is crucial for infrared surveillance, yet remains challenging due to heterogeneous imaging domains and inconsistent target charac…
Probing Deep into Temporal Profile Makes the Infrared Small Target Detector Much Better
Ruojing Li, Wei An, Yingqian Wang +6
Infrared small target (IRST) detection is challenging in simultaneously achieving precise, robust, and efficient performance due to extremely dim targets and strong interference. C…
Towards Robust Infrared Small Target Detection: A Feature-Enhanced and Sensitivity-Tunable Framework
Jinmiao Zhao, Zelin Shi, Chuang Yu +2
Recently, single-frame infrared small target (SIRST) detection technology has attracted widespread attention. Different from most existing deep learning-based methods that focus on…
Event-based Tiny Object Detection: A Benchmark Dataset and Baseline
Nuo Chen, Chao Xiao, Yimian Dai +3
Small object detection (SOD) in anti-UAV task is a challenging problem due to the small size of UAVs and complex backgrounds. Traditional frame-based cameras struggle to detect sma…