RLLNet: a lightweight remaking learning network for saliency redetection on RGB-D images
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s11432-020-3337-9.pdf
Reference9 articles.
1. Zhou W J, Guo Q L, Lei J S, et al. IRFR-Net: interactive recursive feature-reshaping network for detecting salient objects in RGB-D images. IEEE Trans Neural Netw Learn Syst, 2021. doi: https://doi.org/10.1109/TNNLS.2021.3105484
2. Zhou T, Fan D P, Cheng M M, et al. RGB-D salient object detection: a survey. Comp Visual Media, 2021, 7: 37–69
3. Zhou W J, Wu J W, Lei J S, et al. Salient object detection in stereoscopic 3D images using a deep convolutional residual autoencoder. IEEE Trans Multimedia, 2021, 23: 3388–3399
4. Zhang Z, Lin Z, Xu J, et al. Bilateral attention network for RGB-D salient object detection. IEEE Trans Image Process, 2021, 30: 1949–1961
5. Borji A, Cheng M M, Jiang H, et al. Salient object detection: a benchmark. IEEE Trans Image Process, 2015, 24: 5706–5722
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