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NonLocal Channel Attention for NonHomogeneous Image Dehazing
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020The emergence of deep learning methods that complement traditional model-based methods has helped achieve a new state-of-the-art for image dehazing. Many recent methods design deep networks that either estimate the haze-free image (J) directly or estimate physical parameters in the haze model, i.e. ambient light (A) and transmission map (t) followed by
Kareem M. Metwaly +3 more
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IPTV Channel Zapping Recommendation With Attention Mechanism
IEEE Transactions on Multimedia, 2021Internet Protocol TV (IPTV) normally has the advantage of providing far more TV channels than the traditional TV services, while as the other side of the coin it has the problem of information overload. Users of IPTV usually have difficulties finding channels matching their interests.
Guangyu Li +5 more
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DepthWise Attention: Towards Individual Channels Attention
2023 IEEE Symposium on Computers and Communications (ISCC), 2023Zhilei Zhu +3 more
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Partial channel pooling attention beats convolutional attention
Expert Systems with Applications, 2023Jun Zhang 0113, Wushour Slamu
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Scale channel attention network for image segmentation
Multimedia Tools and Applications, 2020The object scale variation results in a negative effect on image segmentation performance. Spatial pyramid pooling module or the attention mechanism are two widely used components in deep neural networks to handle this problem. Applying the single component commonly achieves limited benefit.
Jianjun Chen +4 more
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Learning Spatial-Channel Attention for Visual Tracking
2019 IEEE/CIC International Conference on Communications in China (ICCC), 2019Convolutional neural networks have an advantage of strong representation and has been widely applied to visual tracking. However, simply deepening network in pursuit of boosting performance is inappropriate for tracking because of its speed requirement.
Yingsen Zeng, Haiying Wang 0005, Ting Lu
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On the Division of Attention: A Disproof of the Single Channel Hypothesis
Quarterly Journal of Experimental Psychology, 1972In dichotic listening, subjects are apparently unable to attend simultaneously to two concurrent, auditory speech messages. However, in two experiments reported here, it is shown that people can attend to and repeat back continuous speech at the same time as taking in complex, unrelated visual scenes, or even while sight-reading piano music.
D A, Allport, B, Antonis, P, Reynolds
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Adversarial Training with Channel Attention Regularization
2022 IEEE International Conference on Image Processing (ICIP), 2022Seungju Cho +4 more
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PointNet-Based Channel Attention VLAD Network
2019With the upgrading of application scenarios, computer vision is progressively expanded to 3D. Many methods that process point cloud directly provide a new paradigm for 3D understanding. Most of these methods employ maxpooling to handle the sparsity and disorder of point cloud.
Rongrong Fan +2 more
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GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel Attention
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022Jun Guo, Dongliang Chang, Zhanyu Ma
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