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Ground Penetrating Radar (GPR) has been widely used to estimate the healthy operation of some urban roads and underground facilities. When identifying subsurface anomalies by GPR in an area, the obtained data could be unbalanced, and the…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Xiren Zhou , Shikang Liu , Ao Chen , Yizhan Fan , Huanhuan Chen

Object extraction and segmentation from remote sensing (RS) images is a critical yet challenging task in urban environment monitoring. Urban morphology is inherently complex, with irregular objects of diverse shapes and varying scales.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-24 Chenyu Li , Danfeng Hong , Bing Zhang , Yuxuan Li , Gustau Camps-Valls , Xiao Xiang Zhu , Jocelyn Chanussot

Segment Anything Model (SAM) is an advanced foundational model for image segmentation, which is gradually being applied to remote sensing images (RSIs). Due to the domain gap between RSIs and natural images, traditional methods typically…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Nanqing Liu , Xun Xu , Yongyi Su , Haojie Zhang , Heng-Chao Li

The Segment Anything Model (SAM) is a cornerstone of image segmentation, demonstrating exceptional performance across various applications, particularly in autonomous driving and medical imaging, where precise segmentation is crucial.…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Xiaoliang Liu , Furao Shen , Jian Zhao

Updated building footprints with refugee camps from high-resolution satellite imagery can support related humanitarian operations. This study explores the utilization of the "Segment Anything Model" (SAM) and one of its branches,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Yunya Gao

The development of high-resolution remote sensing satellites has provided great convenience for research work related to remote sensing. Segmentation and extraction of specific targets are essential tasks when facing the vast and complex…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Jie Zhang , Xubing Yang , Rui Jiang , Wei Shao , Li Zhang

While the Segment Anything Model (SAM) has achieved remarkable success in image segmentation, its direct application to medical imaging remains hindered by fundamental challenges, including ambiguous boundaries, insufficient modeling of…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Yu Li , Da Chang , Xi Xiao

Recently segment anything model (SAM) has attracted widespread concerns, and it is often treated as a vision foundation model for universal segmentation. Some researchers have attempted to directly apply the foundation model to the RGB-D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Jia Lin , Xiaofei Zhou , Jiyuan Liu , Runmin Cong , Guodao Zhang , Zhi Liu , Jiyong Zhang

Detecting glass regions is a challenging task due to the ambiguity of their transparency and reflection properties. These transparent glasses share the visual appearance of both transmitted arbitrary background scenes and reflected objects,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Jing Hao , Moyun Liu , Kuo Feng Hung

Ground Penetrating Radar (GPR) has been widely used in pipeline detection and underground diagnosis. In practical applications, the characteristics of the GPR data of the detected area and the likely underground anomalous structures could…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Ao Chen , Xiren Zhou , Yizhan Fan , Huanhuan Chen

The Segment Anything Model (SAM) is a foundation model for general image segmentation. Although it exhibits impressive performance predominantly on natural images, understanding its robustness against various image perturbations and domains…

Computer Vision and Pattern Recognition · Computer Science 2023-05-25 Yuqing Wang , Yun Zhao , Linda Petzold

Segment anything model (SAM) has demonstrated excellent generalizability in common vision scenarios, yet falling short of the ability to understand specialized data. Recently, several methods have combined parameter-efficient techniques…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Yiran Song , Qianyu Zhou , Xuequan Lu , Zhiwen Shao , Lizhuang Ma

Segment Anything Model (SAM), known for its remarkable zero-shot segmentation capabilities, has garnered significant attention in the community. Nevertheless, its performance is challenged when dealing with what we refer to as visually…

Computer Vision and Pattern Recognition · Computer Science 2026-01-05 Guangqian Guo , Pengfei Chen , Yong Guo , Huafeng Chen , Boqiang Zhang , Shan Gao

Weakly supervised landslide extraction aims to identify landslide regions from remote sensing data using models trained with weak labels, particularly image-level labels. However, it is often challenged by the imprecise boundaries of the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Jian Wang , Xiaokang Zhang , Xianping Ma , Weikang Yu , Pedram Ghamisi

Ground Penetrating Radar (GPR) is a widely used Non-Destructive Testing (NDT) technique for subsurface exploration, particularly in infrastructure inspection and maintenance. However, conventional interpretation methods are often limited by…

Signal Processing · Electrical Eng. & Systems 2026-01-15 Meiyan Kang , Shizuo Kaji , Sang-Yun Lee , Taegon Kim , Hee-Hwan Ryu , Suyoung Choi

Recently, large foundation models trained on vast datasets have demonstrated exceptional capabilities in feature extraction and general feature representation. The ongoing advancements in deep learning-driven large models have shown great…

Computer Vision and Pattern Recognition · Computer Science 2025-08-27 Meiqi Hu , Lingzhi Lu , Chengxi Han , Xiaoping Liu

Visual surface anomaly detection aims to detect local image regions that significantly deviate from normal appearance. Recent surface anomaly detection methods rely on generative models to accurately reconstruct the normal areas and to fail…

Computer Vision and Pattern Recognition · Computer Science 2021-09-28 Vitjan Zavrtanik , Matej Kristan , Danijel Skočaj

Ground Penetrating Radar (GPR) is one of the most important non-destructive evaluation (NDE) instruments to detect and locate underground objects (i.e., rebars, utility pipes). Many previous researches focus on GPR image-based feature…

Computer Vision and Pattern Recognition · Computer Science 2021-05-19 Jinglun Feng , Liang Yang , Ejup Hoxha , Diar Sanakov , Stanislav Sotnikov , Jizhong Xiao

Robust and accurate segmentation of scenes has become one core functionality in various visual recognition and navigation tasks. This has inspired the recent development of Segment Anything Model (SAM), a foundation model for general mask…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Aoran Xiao , Weihao Xuan , Heli Qi , Yun Xing , Naoto Yokoya , Shijian Lu

The absence of robust segmentation frameworks for noisy liquid phase transmission electron microscopy (LPTEM) videos prevents reliable extraction of particle trajectories, creating a major barrier to quantitative analysis and to connecting…

Computer Vision and Pattern Recognition · Computer Science 2025-11-06 Alexander Wang , Max Xu , Risha Goel , Zain Shabeeb , Isabel Panicker , Vida Jamali
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