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Advances in deep concealed scene understanding
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 …
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 …
hidden in their surrounding environment, thereby deceiving the human visual system. As an …
Diffusemix: Label-preserving data augmentation with diffusion models
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 …
to improve the generalization of deep neural networks. In these techniques two or more …
Camoformer: Masked separable attention for camouflaged object detection
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 …
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
Camouflaged vision perception is an important vision task with numerous practical
applications. Due to the expensive collection and labeling costs this community struggles …
applications. Due to the expensive collection and labeling costs this community struggles …
A survey on data augmentation in large model era
Large models, encompassing large language and diffusion models, have shown
exceptional promise in approximating human-level intelligence, garnering significant …
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
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; …
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
Recently, zero-shot multi-label classification has garnered considerable attention owing to
its capacity to predict unseen labels without human annotations. Nevertheless, prevailing …
its capacity to predict unseen labels without human annotations. Nevertheless, prevailing …
High-Precision Dichotomous Image Segmentation With Frequency and Scale Awareness
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 …
is a challenging task. Despite the plausible results achieved by deep learning-based …
Meddiffusion: Boosting health risk prediction via diffusion-based data augmentation
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 …
their historical Electronic Health Records (EHR). Although several effective models have …