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 …

Feature shrinkage pyramid for camouflaged object detection with transformers

Z Huang, H Dai, TZ Xiang, S Wang… - Proceedings of the …, 2023 - openaccess.thecvf.com
Vision transformers have recently shown strong global context modeling capabilities in
camouflaged object detection. However, they suffer from two major limitations: less effective …

Cross-level feature aggregation network for polyp segmentation

T Zhou, Y Zhou, K He, C Gong, J Yang, H Fu, D Shen - Pattern Recognition, 2023 - Elsevier
Accurate segmentation of polyps from colonoscopy images plays a critical role in the
diagnosis and cure of colorectal cancer. Although effectiveness has been achieved in the …

Can sam segment anything? when sam meets camouflaged object detection

L Tang, H Xiao, B Li - arXiv preprint arXiv:2304.04709, 2023 - arxiv.org
SAM is a segmentation model recently released by Meta AI Research and has been gaining
attention quickly due to its impressive performance in generic object segmentation …

Feature aggregation and propagation network for camouflaged object detection

T Zhou, Y Zhou, C Gong, J Yang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Camouflaged object detection (COD) aims to detect/segment camouflaged objects
embedded in the environment, which has attracted increasing attention over the past …

Deep gradient learning for efficient camouflaged object detection

GP Ji, DP Fan, YC Chou, D Dai, A Liniger… - Machine Intelligence …, 2023 - Springer
This paper introduces deep gradient network (DGNet), a novel deep framework that exploits
object gradient supervision for camouflaged object detection (COD). It decouples the task …

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, 2023 - 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 …

Zero-shot camouflaged object detection

H Li, CM Feng, Y Xu, T Zhou, L Yao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The goal of Camouflaged object detection (COD) is to detect objects that are visually
embedded in their surroundings. Existing COD methods only focus on detecting …

MSCAF-net: A general framework for camouflaged object detection via learning multi-scale context-aware features

Y Liu, H Li, J Cheng, X Chen - IEEE Transactions on Circuits …, 2023 - ieeexplore.ieee.org
The aim of camouflaged object detection (COD) is to find objects that are hidden in their
surrounding environment. Due to the factors like low illumination, occlusion, small size and …

Toward Deeper Understanding of Camouflaged Object Detection

Y Lv, J Zhang, Y Dai, A Li, N Barnes… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
Preys in the wild evolve to be camouflaged to avoid being recognized by predators. In this
way, camouflage acts as a key defence mechanism across species that is critical to survival …