Semantic image segmentation: Two decades of research

G Csurka, R Volpi, B Chidlovskii - Foundations and Trends® …, 2022 - nowpublishers.com
Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer
vision applications, providing key information for the global understanding of an image. This …

Advances and challenges in deep learning-based change detection for remote sensing images: A review through various learning paradigms

L Wang, M Zhang, X Gao, W Shi - Remote Sensing, 2024 - mdpi.com
Change detection (CD) in remote sensing (RS) imagery is a pivotal method for detecting
changes in the Earth's surface, finding wide applications in urban planning, disaster …

Querying labeled for unlabeled: Cross-image semantic consistency guided semi-supervised semantic segmentation

L Wu, L Fang, X He, M He, J Ma… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Semi-supervised semantic segmentation aims to learn a semantic segmentation model via
limited labeled images and adequate unlabeled images. The key to this task is generating …

Distilling self-supervised vision transformers for weakly-supervised few-shot classification & segmentation

D Kang, P Koniusz, M Cho… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
We address the task of weakly-supervised few-shot image classification and segmentation,
by leveraging a Vision Transformer (ViT) pretrained with self-supervision. Our proposed …

Pseudo-label guided image synthesis for semi-supervised covid-19 pneumonia infection segmentation

F Lyu, M Ye, JF Carlsen, K Erleben… - … on Medical Imaging, 2022 - ieeexplore.ieee.org
Coronavirus disease 2019 (COVID-19) has become a severe global pandemic. Accurate
pneumonia infection segmentation is important for assisting doctors in diagnosing COVID …

A survey on semi-supervised semantic segmentation

A Peláez-Vegas, P Mesejo, J Luengo - ar** with satellite SAR and optical data
S Ge, H Gu, W Su, J Praks… - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
In this study, we introduce an improved semisupervised deep learning approach, and
demonstrate its suitability for modeling the relationship between forest structural parameters …

Fuzzy positive learning for semi-supervised semantic segmentation

P Qiao, Z Wei, Y Wang, Z Wang… - Proceedings of the …, 2023 - openaccess.thecvf.com
Semi-supervised learning (SSL) essentially pursues class boundary exploration with less
dependence on human annotations. Although typical attempts focus on ameliorating the …