6 papers
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios
Tianyi Zhao, Jiawen Xi, Linhui Xiao +4
Visual grounding (VG) localizes target objects in an image from natural-language expressions. In real-world perception, RGB cues often degrade under low illumination and adverse we…
Knowledge-Guided Adversarial Training for Infrared Object Detection via Thermal Radiation Modeling
Shiji Zhao, Shukun Xiong, Maoxun Yuan +6
In complex environments, infrared object detection exhibits broad applicability and stability across diverse scenarios. However, infrared object detection is vulnerable to both com…
Seeing Through the Noise: Improving Infrared Small Target Detection and Segmentation from Noise Suppression Perspective
Maoxun Yuan, Duanni Meng, Ziteng Xi +4
Infrared small target detection and segmentation (IRSTDS) is a critical yet challenging task in defense and civilian applications, owing to the dim, shapeless appearance of targets…
Breaking Self-Attention Failure: Rethinking Query Initialization for Infrared Small Target Detection
Yuteng Liu, Duanni Meng, Yimian Dai +3
Infrared small target detection (IRSTD) faces significant challenges due to low signal-to-noise ratios, extremely small target sizes, and complex cluttered backgrounds. Although DE…
UniRGB-IR: A Unified Framework for Visible-Infrared Semantic Tasks via Adapter Tuning
Maoxun Yuan, Bo Cui, Tianyi Zhao +4
Semantic analysis on visible (RGB) and infrared (IR) images has gained significant attention due to their enhanced accuracy and robustness under challenging conditions including lo…
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…