Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT) networks, which can be mostly attributed to the increasing communication and sensing …
The recently proposed camouflaged object detection (COD) attempts to segment objects that are visually blended into their surroundings, which is extremely complex and difficult in real …
N Liu, N Zhang, K Wan, L Shao… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
Existing state-of-the-art saliency detection methods heavily rely on CNN-based architectures. Alternatively, we rethink this task from a convolution-free sequence-to …
In this paper, we design a simple yet powerful deep network architecture, U 2-Net, for salient object detection (SOD). The architecture of our U 2-Net is a two-level nested U-structure. The …
Deep-learning based salient object detection methods achieve great progress. However, the variable scale and unknown category of salient objects are great challenges all the time …
Y Lv, J Zhang, Y Dai, A Li, B Liu… - Proceedings of the …, 2021 - openaccess.thecvf.com
Camouflage is a key defence mechanism across species that is critical to survival. Common camouflage include background matching, imitating the color and pattern of the …
Being able to learn dense semantic representations of images without supervision is an important problem in computer vision. However, despite its significance, this problem …
Fully convolutional neural networks (FCNs) have shown their advantages in the salient object detection task. However, most existing FCNs-based methods still suffer from coarse …
Although current salient object detection (SOD) works have achieved significant progress, they are limited when it comes to the integrity of the predicted salient regions. We define the …