TY  - EJOU
AU  - Tong, Kunkun 
AU  - Zou, Guchu 
AU  - Tan, Xin 
AU  - Gong, Jingyu 
AU  - Qi, Zhenyi 
AU  - Zhang, Zhizhong 
AU  - Xie, Yuan 
AU  - Ma, Lizhuang 

TI  - Confusing Object Detection: A Survey
T2  - Computers, Materials \& Continua

PY  - 2024
VL  - 80
IS  - 3
SN  - 1546-2226

AB  - Confusing object detection (COD), such as glass, mirrors, and camouflaged objects, represents a burgeoning visual detection task centered on pinpointing and distinguishing concealed targets within intricate backgrounds, leveraging deep learning methodologies. Despite garnering increasing attention in computer vision, the focus of most existing works leans toward formulating task-specific solutions rather than delving into in-depth analyses of methodological structures. As of now, there is a notable absence of a comprehensive systematic review that focuses on recently proposed deep learning-based models for these specific tasks. To fill this gap, our study presents a pioneering review that covers both the models and the publicly available benchmark datasets, while also identifying potential directions for future research in this field. The current dataset primarily focuses on single confusing object detection at the image level, with some studies extending to video-level data. We conduct an in-depth analysis of deep learning architectures, revealing that the current state-of-the-art (SOTA) COD methods demonstrate promising performance in single object detection. We also compile and provide detailed descriptions of widely used datasets relevant to these detection tasks. Our endeavor extends to discussing the limitations observed in current methodologies, alongside proposed solutions aimed at enhancing detection accuracy. Additionally, we deliberate on relevant applications and outline future research trajectories, aiming to catalyze advancements in the field of glass, mirror, and camouflaged object detection.
KW  - Confusing object detection; mirror detection; glass detection; camouflaged object detection; deep learning

DO  - 10.32604/cmc.2024.055327