Advances in deep concealed scene understanding

DP Fan, GP Ji, P Xu, MM Cheng, C Sakaridis… - Visual Intelligence, 2023‏ - Springer
Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive
objects exhibiting camouflage. The current boom in terms of techniques and applications …

A systematic review of image-level camouflaged object detection with deep learning

Y Liang, G Qin, M Sun, X Wang, J Yan, Z Zhang - Neurocomputing, 2024‏ - Elsevier
Camouflaged object detection (COD) aims to search and identify disguised objects that are
hidden in their surrounding environment, thereby deceiving the human visual system. As an …

Diffusemix: Label-preserving data augmentation with diffusion models

K Islam, MZ Zaheer, A Mahmood… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Recently a number of image-mixing-based augmentation techniques have been introduced
to improve the generalization of deep neural networks. In these techniques two or more …

Camoformer: Masked separable attention for camouflaged object detection

B Yin, X Zhang, DP Fan, S Jiao… - … on Pattern Analysis …, 2024‏ - ieeexplore.ieee.org
How to identify and segment camouflaged objects from the background is challenging.
Inspired by the multi-head self-attention in Transformers, we present a simple masked …

Lake-red: Camouflaged images generation by latent background knowledge retrieval-augmented diffusion

P Zhao, P Xu, P Qin, DP Fan, Z Zhang… - Proceedings of the …, 2024‏ - openaccess.thecvf.com
Camouflaged vision perception is an important vision task with numerous practical
applications. Due to the expensive collection and labeling costs this community struggles …

A survey on data augmentation in large model era

Y Zhou, C Guo, X Wang, Y Chang, Y Wu - arxiv preprint arxiv:2401.15422, 2024‏ - arxiv.org
Large models, encompassing large language and diffusion models, have shown
exceptional promise in approximating human-level intelligence, garnering significant …

Advances in diffusion models for image data augmentation: A review of methods, models, evaluation metrics and future research directions

P Alimisis, I Mademlis, P Radoglou-Grammatikis… - Artificial Intelligence …, 2025‏ - Springer
Image data augmentation constitutes a critical methodology in modern computer vision
tasks, since it can facilitate towards enhancing the diversity and quality of training datasets; …

Diverse and tailored image generation for zero-shot multi-label classification

K Zhang, Z Yuan, T Huang - Knowledge-Based Systems, 2024‏ - Elsevier
Recently, zero-shot multi-label classification has garnered considerable attention owing to
its capacity to predict unseen labels without human annotations. Nevertheless, prevailing …

High-Precision Dichotomous Image Segmentation With Frequency and Scale Awareness

Q Jiang, J Cheng, Z Wu, R Cong… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
Dichotomous image segmentation (DIS) with rich fine-grained details within a single image
is a challenging task. Despite the plausible results achieved by deep learning-based …

Meddiffusion: Boosting health risk prediction via diffusion-based data augmentation

Y Zhong, S Cui, J Wang, X Wang, Z Yin, Y Wang… - Proceedings of the 2024 …, 2024‏ - SIAM
Health risk prediction aims to forecast the potential health risks that patients may face using
their historical Electronic Health Records (EHR). Although several effective models have …