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20152022
most citedDense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images

348 citations · 726 across the 30 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

cs.CV2020★ 348 cited

Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images

Qijian Zhang, Runmin Cong, Chongyi Li +5

Despite the remarkable advances in visual saliency analysis for natural scene images (NSIs), salient object detection (SOD) for optical remote sensing images (RSIs) still remains a…

cs.LG2020

A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

Moloud Abdar, Farhad Pourpanah, Sadiq Hussain +9

Uncertainty quantification (UQ) plays a pivotal role in reduction of uncertainties during both optimization and decision making processes. It can be applied to solve a variety of r…

cs.CR2020★ 8 cited

Adv-watermark: A Novel Watermark Perturbation for Adversarial Examples

Xiaojun Jia, Xingxing Wei, Xiaochun Cao +1

Recent research has demonstrated that adding some imperceptible perturbations to original images can fool deep learning models. However, the current adversarial perturbations are u…

eess.IV2020★ 85 cited

Single Image Super-Resolution via a Holistic Attention Network

Ben Niu, Weilei Wen, Wenqi Ren +6

Informative features play a crucial role in the single image super-resolution task. Channel attention has been demonstrated to be effective for preserving information-rich features…

cs.CV2020★ 3 cited

Efficient Adversarial Attacks for Visual Object Tracking

Siyuan Liang, Xingxing Wei, Siyuan Yao +1

Visual object tracking is an important task that requires the tracker to find the objects quickly and accurately. The existing state-ofthe-art object trackers, i.e., Siamese based…

cs.CV2020

Face Super-Resolution Guided by 3D Facial Priors

Xiaobin Hu, Wenqi Ren, John LaMaster +5

State-of-the-art face super-resolution methods employ deep convolutional neural networks to learn a mapping between low- and high- resolution facial patterns by exploring local app…