[HTML][HTML] 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 …

Weakly-supervised concealed object segmentation with sam-based pseudo labeling and multi-scale feature grouping

C He, K Li, Y Zhang, G Xu, L Tang… - Advances in …, 2024 - proceedings.neurips.cc
Abstract Weakly-Supervised Concealed Object Segmentation (WSCOS) aims to segment
objects well blended with surrounding environments using sparsely-annotated data for …

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 …

Diffusion model for camouflaged object detection

Z Chen, R Gao, TZ Xiang, F Lin - ECAI 2023, 2023 - ebooks.iospress.nl
Camouflaged object detection is a challenging task that aims to identify objects that are
highly similar to their background. Due to the powerful noise-to-image denoising capability …

Scribformer: Transformer makes cnn work better for scribble-based medical image segmentation

Z Li, Y Zheng, D Shan, S Yang, Q Li… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
Most recent scribble-supervised segmentation methods commonly adopt a CNN framework
with an encoder-decoder architecture. Despite its multiple benefits, this framework generally …

Predictive uncertainty estimation for camouflaged object detection

Y Zhang, J Zhang, W Hamidouche… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Uncertainty is inherent in machine learning methods, especially those for camouflaged
object detection aiming to finely segment the objects concealed in background. The strong …

Referring camouflaged object detection

X Zhang, B Yin, Z Lin, Q Hou, DP Fan… - arXiv preprint arXiv …, 2023 - arxiv.org
In this paper, we consider the problem of referring camouflaged object detection (Ref-COD),
a new task that aims to segment specified camouflaged objects based on some form of …

Extraordinary MHNet: Military high-level camouflage object detection network and dataset

M Liu, X Di - Neurocomputing, 2023 - Elsevier
We present the first systematic work on Military High-level Camouflage object Detection
(MHCD), aiming to identify objects visibly embedded in chaotic backgrounds. The high …

Chain of visual perception: Harnessing multimodal large language models for zero-shot camouflaged object detection

L Tang, PT Jiang, Z Shen, H Zhang, J Chen… - ACM Multimedia …, 2024 - openreview.net
In this paper, we introduce a novel multimodal camo-perceptive framework (MMCPF) aimed
at handling zero-shot Camouflaged Object Detection (COD) by leveraging the powerful …