5 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…
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…
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…
Removal then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object Detection
Tianyi Zhao, Maoxun Yuan, Feng Jiang +2
In recent years, object detection utilizing both visible (RGB) and thermal infrared (IR) imagery has garnered extensive attention and has been widely implemented across a diverse a…