11.2.4.5 RGB-D Salient Object Segmentation and Detection

Chapter Contents (Back)
Range Segmentation. RGB-D Segmentation. Salient Objects.
See also Range and Color, RGB-D Segmentation and Analysis.
See also Salient Regions, Saliencey for Regions.
See also Depth Object Segmentation, Point Cloud Segmentation.
See also Semantic Object Detection, 3D, Depth.

Cong, R.M.[Run-Min], Lei, J.J.[Jian-Jun], Zhang, C.Q.[Chang-Qing], Huang, Q.M.[Qing-Ming], Cao, X.C.[Xiao-Chun], Hou, C.P.[Chun-Ping],
Saliency Detection for Stereoscopic Images Based on Depth Confidence Analysis and Multiple Cues Fusion,
SPLetters(23), No. 6, June 2016, pp. 819-823.
IEEE DOI 1606
Computational modeling BibRef

Cong, R.M.[Run-Min], Lei, J.J.[Jian-Jun], Fu, H.Z.[Hua-Zhu], Huang, Q.M.[Qing-Ming], Cao, X.C.[Xiao-Chun], Hou, C.P.[Chun-Ping],
Co-Saliency Detection for RGBD Images Based on Multi-Constraint Feature Matching and Cross Label Propagation,
IP(27), No. 2, February 2018, pp. 568-579.
IEEE DOI 1712
Computational modeling, Feature extraction, Image segmentation, Optimization, Robustness, multi-constraint BibRef

Cong, R.M.[Run-Min], Lei, J.J.[Jian-Jun], Fu, H.Z.[Hua-Zhu], Porikli, F.M.[Fatih M.], Huang, Q.M.[Qing-Ming], Hou, C.P.[Chun-Ping],
Video Saliency Detection via Sparsity-Based Reconstruction and Propagation,
IP(28), No. 10, October 2019, pp. 4819-4831.
IEEE DOI 1909
feature extraction, image motion analysis, image reconstruction, image sampling, image sequences, object detection, global optimization BibRef

Zhang, T.H.[Tian-Hao], Zhou, Y.[Yuan], Huo, S.W.[Shu-Wei], Hou, C.P.[Chun-Ping],
Label propagation based saliency detection via graph design,
ICIP17(460-464)
IEEE DOI 1803
Color, Image color analysis, Image edge detection, Reliability, Saliency detection, Task analysis, Visualization, Saliency detection BibRef

Cong, R.M.[Run-Min], Lei, J.J.[Jian-Jun], Fu, H.Z.[Hua-Zhu], Huang, Q.M.[Qing-Ming], Cao, X.C.[Xiao-Chun], Ling, N.[Nam],
HSCS: Hierarchical Sparsity Based Co-saliency Detection for RGBD Images,
MultMed(21), No. 7, July 2019, pp. 1660-1671.
IEEE DOI 1906
Saliency detection, Image reconstruction, Dictionaries, Feature extraction, Task analysis, energy function refinement BibRef

Cong, R.M.[Run-Min], Lei, J.J.[Jian-Jun], Fu, H.Z.[Hua-Zhu], Hou, J.H.[Jun-Hui], Huang, Q.M.[Qing-Ming], Kwong, S.[Sam],
Going From RGB to RGBD Saliency: A Depth-Guided Transformation Model,
Cyber(50), No. 8, August 2020, pp. 3627-3639.
IEEE DOI 2007
Saliency detection, Image color analysis, Optimization, Shape, Feature extraction, Task analysis, Object detection, Depth cue, transformation model BibRef

Liu, C., Zhou, W., Chen, Y., Lei, J.,
Asymmetric Deeply Fused Network for Detecting Salient Objects in RGB-D Images,
SPLetters(27), 2020, pp. 1620-1624.
IEEE DOI 2010
Feature extraction, Decoding, Convolution, Adaptation models, Fuses, Visualization, Object detection, RGB-D, adaptive attention transformer module BibRef

Cong, R.M.[Run-Min], Lin, Q.[Qinwei], Zhang, C.[Chen], Li, C.Y.[Chong-Yi], Cao, X.C.[Xiao-Chun], Huang, Q.M.[Qing-Ming], Zhao, Y.[Yao],
CIR-Net: Cross-Modality Interaction and Refinement for RGB-D Salient Object Detection,
IP(31), 2022, pp. 6800-6815.
IEEE DOI 2211
Decoding, Task analysis, Periodic structures, Middleware, Logic gates, Electronic mail, Object detection, cross-modality interaction BibRef

Li, C.Y.[Chong-Yi], Cong, R.M.[Run-Min], Piao, Y.[Yongri], Xu, Q.Q.[Qian-Qian], Loy, C.C.[Chen Change],
RGB-D Salient Object Detection with Cross-modality Modulation and Selection,
ECCV20(VIII:225-241).
Springer DOI 2011
BibRef

Zhang, Q.[Qiang], Xiao, T.L.[Tong-Lin], Huang, N.C.[Nian-Chang], Zhang, D.W.[Ding-Wen], Han, J.G.[Jun-Gong],
Revisiting Feature Fusion for RGB-T Salient Object Detection,
CirSysVideo(31), No. 5, 2021, pp. 1804-1818.
IEEE DOI 2105
BibRef

Huang, N.C.[Nian-Chang], Liu, Y.[Yi], Zhang, Q.[Qiang], Han, J.G.[Jun-Gong],
Joint Cross-Modal and Unimodal Features for RGB-D Salient Object Detection,
MultMed(23), 2021, pp. 2428-2441.
IEEE DOI 2108
Feature extraction, Saliency detection, Object detection, Computational modeling, Task analysis, multi-branch feature fusion and feature selection BibRef

Huang, N.Z.[Nian-Zchang], Luo, Y.J.[Yong-Jiang], Zhang, Q.[Qiang], Han, J.G.[Jun-Gong],
Discriminative unimodal feature selection and fusion for RGB-D salient object detection,
PR(122), 2022, pp. 108359.
Elsevier DOI 2112
RGB-D salient object detection, Discriminative unimodal feature selection, Multi-scale cross-modal feature fusion BibRef

Huang, N.C.[Nian-Chang], Jiao, Q.[Qiang], Zhang, Q.[Qiang], Han, J.G.[Jun-Gong],
Middle-Level Feature Fusion for Lightweight RGB-D Salient Object Detection,
IP(31), 2022, pp. 6621-6634.
IEEE DOI 2211
Feature extraction, Periodic structures, Data mining, Computational modeling, Object detection, Fuses, Semantics, feature-level and decision-level information mutual guidance BibRef

Li, C.Y.[Chong-Yi], Cong, R.M.[Run-Min], Kwong, S.[Sam], Hou, J.H.[Jun-Hui], Fu, H.Z.[Hua-Zhu], Zhu, G.P.[Guo-Pu], Zhang, D.W.[Ding-Wen], Huang, Q.M.[Qing-Ming],
ASIF-Net: Attention Steered Interweave Fusion Network for RGB-D Salient Object Detection,
Cyber(51), No. 1, January 2021, pp. 88-100.
IEEE DOI 2012
Feature extraction, Saliency detection, Object detection, Task analysis, Fuses, Random access memory, Semantics, saliency detection BibRef

Zhai, Y.J.[Ying-Jie], Fan, D.P.[Deng-Ping], Yang, J.F.[Ju-Feng], Borji, A.[Ali], Shao, L.[Ling], Han, J.W.[Jun-Wei], Wang, L.[Liang],
Bifurcated Backbone Strategy for RGB-D Salient Object Detection,
IP(30), 2021, pp. 8727-8742.
IEEE DOI 2111
BibRef
Earlier: A2, A1, A4, A3, A5, Only:
BBS-Net: RGB-D Salient Object Detection with a Bifurcated Backbone Strategy Network,
ECCV20(275-292).
Springer DOI 2010
Feature extraction, Semantics, Decoding, Training, Object detection, Data mining, Image color analysis, cascaded refinement
See also Deeply Supervised Salient Object Detection with Short Connections. BibRef

Jin, W.D.[Wen-Da], Xu, J.[Jun], Han, Q.[Qi], Zhang, Y.[Yi], Cheng, M.M.[Ming-Ming],
CDNet: Complementary Depth Network for RGB-D Salient Object Detection,
IP(30), 2021, pp. 3376-3390.
IEEE DOI 2103
Feature extraction, Ions, Fuses, Task analysis, Object detection, Streaming media, Predictive models, cross-modal feature fusion BibRef

Zhang, Z.[Zhao], Lin, Z.[Zheng], Xu, J.[Jun], Jin, W.D.[Wen-Da], Lu, S.P.[Shao-Ping], Fan, D.P.[Deng-Ping],
Bilateral Attention Network for RGB-D Salient Object Detection,
IP(30), 2021, pp. 1949-1961.
IEEE DOI 2101
Feature extraction, Object detection, Image color analysis, Fans, Benchmark testing, Task analysis, Streaming media, RGB-D image BibRef

Fu, K.[Keren], Fan, D.P.[Deng-Ping], Ji, G.P.[Ge-Peng], Zhao, Q.J.[Qi-Jun], Shen, J.B.[Jian-Bing], Zhu, C.[Ce],
Siamese Network for RGB-D Salient Object Detection and Beyond,
PAMI(44), No. 9, September 2022, pp. 5541-5559.
IEEE DOI 2208
Feature extraction, Task analysis, Computational modeling, Semantics, Object detection, Computer architecture, RGB-D semantic segmentation BibRef

Chen, G.[Geng], Fu, H.Z.[Hua-Zhu], Zhou, T.[Tao], Xiao, G.[Guobao], Fu, K.[Keren], Xia, Y.[Yong], Zhang, Y.N.[Yan-Ning],
Fusion-Embedding Siamese Network for Light Field Salient Object Detection,
MultMed(26), 2024, pp. 984-994.
IEEE DOI 2402
Feature extraction, Decoding, Transformers, Saliency detection, Transforms, Data models, Object detection, Light field BibRef

Wen, H.F.[Hong-Fa], Yan, C.G.[Cheng-Gang], Zhou, X.F.[Xiao-Fei], Cong, R.M.[Run-Min], Sun, Y.Q.[Yao-Qi], Zheng, B.[Bolun], Zhang, J.Y.[Ji-Yong], Bao, Y.J.[Yong-Jun], Ding, G.G.[Gui-Guang],
Dynamic Selective Network for RGB-D Salient Object Detection,
IP(30), 2021, pp. 9179-9192.
IEEE DOI 2112
Feature extraction, Semantics, Object detection, Deep learning, Saliency detection, Logic gates, feature fusion BibRef

Song, H.[Hangke], Liu, Z.[Zhi], Xie, Y.F.[Yu-Feng], Wu, L.S.[Li-Shan], Huang, M.[Mengke],
RGBD Co-Saliency Detection via Bagging-Based Clustering,
SPLetters(23), No. 12, December 2016, pp. 1722-1726.
IEEE DOI 1612
feature extraction BibRef

Tang, Y.L.[Yan-Long], Tong, R.F.[Ruo-Feng], Tang, M.[Min], Zhang, Y.[Yun],
Depth incorporating with color improves salient object detection,
VC(32), No. 1, January 2016, pp. 111-121.
WWW Link. 1602
BibRef

Ye, L.W.[Lin-Wei], Liu, Z.[Zhi], Li, L.[Lina], Shen, L.Q.[Li-Quan], Bai, C.[Cong], Wang, Y.[Yang],
Salient Object Segmentation via Effective Integration of Saliency and Objectness,
MultMed(19), No. 8, August 2017, pp. 1742-1756.
IEEE DOI 1708
Benchmark testing, Computer science, Image color analysis, Image edge detection, Image segmentation, Object segmentation, Predictive models, Graph-based integration, object probability, objectness map, saliency map, salient, object, segmentation BibRef

Song, H.K.[Hang-Ke], Liu, Z.[Zhi], Du, H.[Huan], Sun, G.L.[Guang-Ling], Le Meur, O.[Olivier], Ren, T.W.[Tong-Wei],
Depth-Aware Salient Object Detection and Segmentation via Multiscale Discriminative Saliency Fusion and Bootstrap Learning,
IP(26), No. 9, September 2017, pp. 4204-4216.
IEEE DOI 1708
computer bootstrapping, feature extraction, image colour analysis, image fusion, image segmentation, learning (artificial intelligence), regression analysis, stereo image processing, DSF saliency map, depth maps, depth-aware salient object detection and segmentation framework, discriminative saliency fusion, high-level location priors, mid-level feature weighted factors, multiscale region segmentation, random forest regressor, discriminative saliency fusion BibRef

Imamoglu, N.[Nevrez], Shimoda, W.[Wataru], Zhang, C.[Chi], Fang, Y.M.[Yu-Ming], Kanezaki, A.[Asako], Yanai, K.[Keiji], Nishida, Y.[Yoshifumi],
An integration of bottom-up and top-down salient cues on RGB-D data: saliency from objectness versus non-objectness,
SIViP(12), No. 2, February 2018, pp. 307-314.
Springer DOI 1802
BibRef

Xu, H.B.[Hai-Bo], Zhang, G.[Ge], Zhang, Q.M.[Qing-Ming],
Retracted: An iterative propagation based co-saliency framework for RGBD images,
JVCIR(77), 2021, pp. 103083.
Elsevier DOI 2106
BibRef
And: Originally: JVCIR(59), 2019, pp. 186-194.
Elsevier DOI 1903
RGBD images, Co-saliency, Iterative optimization, Saliency propagation, Depth information, Saliency detection BibRef

Jiang, Y.[Yibo], Bi, H.[Hui], Li, H.[Hui], Xu, Z.H.[Zhi-Hao],
Automatic and Accurate 3D Measurement Based on RGBD Saliency Detection,
IEICE(E102-D), No. 3, March 2019, pp. 688-689.
WWW Link. 1904
BibRef

Ding, Y.[Yu], Liu, Z.[Zhi], Huang, M.[Mengke], Shi, R.[Ran], Wang, X.Y.[Xiang-Yang],
Depth-Aware Saliency Detection Using Convolutional Neural Networks,
JVCIR(61), 2019, pp. 1-9.
Elsevier DOI 1906
Saliency detection, Convolutional neural networks, Depth saliency network, Saliency fusion network, RGBD images, Stereoscopic images BibRef

Yuan, J.[Jing], Cao, Y.[Yang], Kang, Y.[Yu], Song, W.G.[Wei-Guo], Yin, Z.C.[Zhong-Cheng], Ba, R.[Rui], Ma, Q.[Qing],
3D Layout encoding network for spatial-aware 3D saliency modelling,
IET-CV(13), No. 5, August 2019, pp. 480-488.
DOI Link 1908
RGB-D saliency, deal with low quality D from such sensors. BibRef

Chen, C., Wei, J., Peng, C., Zhang, W., Qin, H.,
Improved Saliency Detection in RGB-D Images Using Two-Phase Depth Estimation and Selective Deep Fusion,
IP(29), 2020, pp. 4296-4307.
IEEE DOI 2002
RGB-D saliency detection, inter-image correspondences, low-level saliency, selective deep fusion BibRef

Pan, L.[Liang], Zhou, X.F.[Xiao-Fei], Shi, R.[Ran], Zhang, J.Y.[Ji-Yong], Yan, C.G.[Cheng-Gang],
Cross-modal feature extraction and integration based RGBD saliency detection,
IVC(101), 2020, pp. 103964.
Elsevier DOI 2009
RGBD, Saliency, Cross-modal, Feature extraction, Integration BibRef

Luo, A.[Ao], Li, X.[Xin], Yang, F.[Fan], Jiao, Z.C.[Zhi-Cheng], Cheng, H.[Hong], Lyu, S.W.[Si-Wei],
Cascade Graph Neural Networks for RGB-D Salient Object Detection,
ECCV20(XII: 346-364).
Springer DOI 2010
BibRef

Niu, Y., Long, G., Liu, W., Guo, W., He, S.,
Boundary-Aware RGBD Salient Object Detection With Cross-Modal Feature Sampling,
IP(29), 2020, pp. 9496-9507.
IEEE DOI 1806
Object detection, Image color analysis, Merging, Feature extraction, Fuses, Image edge detection, Estimation, boundary-aware estimation BibRef

Liang, F.F.[Fang-Fang], Duan, L.J.[Li-Juan], Ma, W.[Wei], Qiao, Y.H.[Yuan-Hua], Miao, J.[Jun], Ye, Q.X.[Qi-Xiang],
Context-aware network for RGB-D salient object detection,
PR(111), 2021, pp. 107630.
Elsevier DOI 2012
Stereoscopic saliency analysis, 3D images, Multi-modal context fusion, Context-dependent deconvolution BibRef

Liang, F.F.[Fang-Fang], Duan, L.J.[Li-Juan], Ma, W.[Wei], Qiao, Y.H.[Yuan-Hua], Cai, Z.[Zhi], Miao, J.[Jun], Ye, Q.X.[Qi-Xiang],
CoCNN: RGB-D deep fusion for stereoscopic salient object detection,
PR(104), 2020, pp. 107329.
Elsevier DOI 2005
Coupled CNN, Cascaded span network, Stereoscopic images, Salient object detection BibRef

Huang, R., Xing, Y., Zou, Y.,
Triple-Complementary Network for RGB-D Salient Object Detection,
SPLetters(27), 2020, pp. 775-779.
IEEE DOI 2006
RGB-D saliency detection, saliency fusion, triple-complementary network BibRef

Zhou, W.J.[Wu-Jie], Chen, Y.Z.[Yu-Zhen], Liu, C.[Chang], Yu, L.[Lu],
GFNet: Gate Fusion Network With Res2Net for Detecting Salient Objects in RGB-D Images,
SPLetters(27), 2020, pp. 800-804.
IEEE DOI 2006
Logic gates, Feature extraction, Convolution, Training, Detectors, Object detection, Decoding, Gate fusion network, gate mechanism, salient object detection BibRef

Zhou, Y.[Yang], Liu, X.Q.[Xiao-Qi], Zhang, Y.[Yun], Yin, H.B.[Hai-Bing], Lu, Y.[Yu],
Salient object detection via reliability-based depth compactness and depth contrast,
IET-IPR(14), No. 14, December 2020, pp. 3623-3631.
DOI Link 2012
BibRef

Guo, Q.L.[Qin-Ling], Zhou, W.[Wujie], Lei, J.S.[Jing-Sheng], Yu, L.[Lu],
TSFNet: Two-Stage Fusion Network for RGB-T Salient Object Detection,
SPLetters(28), 2021, pp. 1655-1659.
IEEE DOI 2109
Feature extraction, Object detection, Computational modeling, Image segmentation, Encoding, Decoding, Benchmark testing, RGB-T, feature-wise fusion module BibRef

Zhou, W.[Wujie], Guo, Q.L.[Qin-Ling], Lei, J.S.[Jing-Sheng], Yu, L.[Lu], Hwang, J.N.[Jenq-Neng],
ECFFNet: Effective and Consistent Feature Fusion Network for RGB-T Salient Object Detection,
CirSysVideo(32), No. 3, March 2022, pp. 1224-1235.
IEEE DOI 2203
Feature extraction, Decoding, Streaming media, Imaging, Sorting, Meteorology, Lighting, RGB-T data, salient object detection, multilevel consistent fusion module BibRef

Zhou, W.[Wujie], Zhu, Y.[Yun], Lei, J.S.[Jing-Sheng], Wan, J.[Jian], Yu, L.[Lu],
CCAFNet: Crossflow and Cross-Scale Adaptive Fusion Network for Detecting Salient Objects in RGB-D Images,
MultMed(24), No. 2022, pp. 2192-2204.
IEEE DOI 2204
Feature extraction, Semantics, Adaptation models, Data mining, Streaming media, Predictive models, Logic gates, spatial fusion module BibRef

Zhou, W.[Wujie], Pan, S.[Sijia], Lei, J.S.[Jing-Sheng], Yu, L.[Lu],
MRINet: Multilevel Reverse-Context Interactive-Fusion Network for Detecting Salient Objects in RGB-D Images,
SPLetters(28), 2021, pp. 1525-1529.
IEEE DOI 2108
Feature extraction, Fuses, Convolution, Semantics, Saliency detection, Magnetic resonance imaging, Training, deep learning BibRef

Zhang, X.Y.[Xin-Yue], Jin, T.[Ting], Zhou, W.J.[Wu-Jie], Lei, J.S.[Jing-Sheng],
Attention-based contextual interaction asymmetric network for RGB-D saliency prediction,
JVCIR(74), 2021, pp. 102997.
Elsevier DOI 2101
RGB-D image, Saliency prediction, Attention mechanism, Contextual interaction BibRef

Chen, Q.[Qian], Fu, K.[Keren], Liu, Z.[Ze], Chen, G.[Geng], Du, H.W.[Hong-Wei], Qiu, B.[Bensheng], Shao, L.[Ling],
EF-Net: A novel enhancement and fusion network for RGB-D saliency detection,
PR(112), 2021, pp. 107740.
Elsevier DOI 2102
Salient object detection, RGB-D image, Depth enhancement, Feature fusion BibRef

Chen, C., Wei, J., Peng, C., Qin, H.,
Depth-Quality-Aware Salient Object Detection,
IP(30), 2021, pp. 2350-2363.
IEEE DOI 2102
image colour analysis, image fusion, object detection, fusion-based RGB-D salient object detection, weakly supervised learning BibRef

Liu, D.[Di], Zhang, K.[Kao], Chen, Z.Z.[Zhen-Zhong],
Attentive Cross-Modal Fusion Network for RGB-D Saliency Detection,
MultMed(23), 2021, pp. 967-981.
IEEE DOI 2103
Object detection, Saliency detection, Feature extraction, Fuses, Visualization, Computational modeling, Semantics, RGB-D salient object detection BibRef

Liu, D.[Di], Hu, Y.[Yaosi], Zhang, K.[Kao], Chen, Z.Z.[Zhen-Zhong],
Two-Stream Refinement Network for RGB-D Saliency Detection,
ICIP19(3925-3929)
IEEE DOI 1910
Two-stream Network, Deep Learning, Fusion Refinement Module, RGB-D Saliency, Propagation-based Refinement BibRef

Zhou, W.[Wujie], Lv, Y.[Ying], Lei, J.S.[Jing-Sheng], Yu, L.[Lu],
Global and Local-Contrast Guides Content-Aware Fusion for RGB-D Saliency Prediction,
SMCS(51), No. 6, June 2021, pp. 3641-3649.
IEEE DOI 2106
Feature extraction, Predictive models, Fuses, Convolution, Visualization, Image resolution, Deep learning, Contrast feature, RGB-D saliency prediction BibRef

Zhu, Y.[Yun], Zhou, W.[Wujie], Li, Q.[Qiang], Yu, L.[Lu],
Parallax-Estimation-Enhanced Network With Interweave Consistency Feature Fusion for Binocular Salient Object Detection,
SPLetters(28), 2021, pp. 927-931.
IEEE DOI 2106
Hafnium, Parallax estimation enhancement, salient object detection, interweave consistency fusion, binocular image BibRef

Chen, H.[Hao], Li, Y.F.[You-Fu], Deng, Y.J.[Yong-Jian], Lin, G.S.[Guo-Sheng],
CNN-Based RGB-D Salient Object Detection: Learn, Select, and Fuse,
IJCV(129), No. 7, July 2021, pp. 2076-2096.
Springer DOI 2106
BibRef

Deng, S.[Shuang], Dong, Q.[Qiulei],
GA-NET: Global Attention Network for Point Cloud Semantic Segmentation,
SPLetters(28), 2021, pp. 1300-1304.
IEEE DOI 2107
Feature extraction, Semantics, Computational complexity, Vegetation mapping, Image segmentation, deep learning BibRef

Chen, Z.[Zuyao], Cong, R.[Runmin], Xu, Q.Q.[Qian-Qian], Huang, Q.M.[Qing-Ming],
DPANet: Depth Potentiality-Aware Gated Attention Network for RGB-D Salient Object Detection,
IP(30), 2021, pp. 7012-7024.
IEEE DOI 2108
Logic gates, Object detection, Contamination, Task analysis, Saliency detection, Computer science, Image color analysis, gated multi-modality attention BibRef

Zhou, W.J.[Wu-Jie], Wu, J.W.[Jun-Wei], Lei, J.S.[Jing-Sheng], Hwang, J.N.[Jenq-Neng], Yu, L.[Lu],
Salient Object Detection in Stereoscopic 3D Images Using a Deep Convolutional Residual Autoencoder,
MultMed(23), 2021, pp. 3388-3399.
IEEE DOI 2109
Object detection, Feature extraction, Saliency detection, convolutional residual neural networks BibRef

Yao, C.[Cuili], Feng, L.[Lin], Kong, Y.Q.[Yu-Qiu], Li, S.M.[Sheng-Ming], Li, H.[Hang],
Double cross-modality progressively guided network for RGB-D salient object detection,
IVC(117), 2022, pp. 104351.
Elsevier DOI 2112
RGB-D, Salient object detection, Cross-modality, Attention mechanism, Integration BibRef

Kong, Y.Q.[Yu-Qiu], Zheng, Y.S.[Yu-Shuo], Yao, C.L.[Cui-Li], Liu, Y.[Yang], Wang, H.[He],
Scale Adaptive Fusion Network for RGB-D Salient Object Detection,
ACCV22(III:608-625).
Springer DOI 2307
BibRef

Wang, X.Q.[Xiao-Qiang], Zhu, L.[Lei], Tang, S.L.[Si-Liang], Fu, H.Z.[Hua-Zhu], Li, P.[Ping], Wu, F.[Fei], Yang, Y.[Yi], Zhuang, Y.T.[Yue-Ting],
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB Images,
IP(31), 2022, pp. 1107-1119.
IEEE DOI 2201
Feature extraction, Saliency detection, Estimation, Fuses, Object detection, Convolutional neural networks, Training, attention consistency BibRef

Wang, F.Y.[Feng-Yun], Pan, J.S.[Jin-Shan], Xu, S.K.[Shou-Kun], Tang, J.H.[Jin-Hui],
Learning Discriminative Cross-Modality Features for RGB-D Saliency Detection,
IP(31), 2022, pp. 1285-1297.
IEEE DOI 2202
Feature extraction, Correlation, Saliency detection, Fuses, Convolution, Task analysis, Object detection, correlation-fusion BibRef

Zhu, J.C.[Jin-Chao], Zhang, X.Y.[Xiao-Yu], Fang, X.[Xian], Dong, F.[Feng], Qiu, Y.[Yu],
Modal-Adaptive Gated Recoding Network for RGB-D Salient Object Detection,
SPLetters(29), 2022, pp. 359-363.
IEEE DOI 2202
Mixers, Logic gates, Decoding, Feature extraction, Semantics, Training, Object detection, Salient object detection, multi-modal, feature fusion BibRef

Fang, X.[Xian], Jiang, M.F.[Ming-Feng], Zhu, J.C.[Jin-Chao], Shao, X.L.[Xiu-Li], Wang, H.P.[Hong-Peng],
M2RNet: Multi-modal and multi-scale refined network for RGB-D salient object detection,
PR(135), 2023, pp. 109139.
Elsevier DOI 2212
Saliency detection, Deep learning, Multi-modal feature, Multi-scale feature, Loss function BibRef

Yi, K.[Kang], Zhu, J.C.[Jin-Chao], Guo, F.[Fu], Xu, J.[Jing],
Cross-Stage Multi-Scale Interaction Network for RGB-D Salient Object Detection,
SPLetters(29), 2022, pp. 2402-2406.
IEEE DOI 2212
Convolution, Object detection, Feature extraction, Strips, Measurement, Kernel, Fuses, Salient object detection, RGB-D, multi-scale BibRef

Zhou, X.F.[Xiao-Fei], Wen, H.F.[Hong-Fa], Shi, R.[Ran], Yin, H.B.[Hai-Bing], Zhang, J.Y.[Ji-Yong], Yan, C.G.[Cheng-Gang],
FANet: Feature aggregation network for RGBD saliency detection,
SP:IC(102), 2022, pp. 116591.
Elsevier DOI 2202
RGBD saliency, Feature aggregation, Graph neural networks, Hierarchical fusion BibRef

Zhang, Y.F.[Yuan-Fang], Zheng, J.B.[Jiang-Bin], Jia, W.J.[Wen-Jing], Huang, W.F.[Wen-Feng], Li, L.[Long], Liu, N.[Nianz], Li, F.[Fei], He, X.J.[Xiang-Jian],
Deep RGB-D Saliency Detection Without Depth,
MultMed(24), 2022, pp. 755-767.
IEEE DOI 2202
Feature extraction, Saliency detection, Fuses, Decoding, Computational modeling, Predictive models, Visualization, saliency detection BibRef

Huang, N.Z.[Nian-Zchang], Yang, Y.[Yang], Zhang, D.W.[Ding-Wen], Zhang, Q.[Qiang], Han, J.G.[Jun-Gong],
Employing Bilinear Fusion and Saliency Prior Information for RGB-D Salient Object Detection,
MultMed(24), 2022, pp. 1651-1664.
IEEE DOI 2204
Feature extraction, Saliency detection, Cognition, Task analysis, Object detection, Computational modeling, Visualization, saliency refinement and prediction BibRef

Gao, W.[Wei], Liao, G.[Guibiao], Ma, S.W.[Si-Wei], Li, G.[Ge], Liang, Y.S.[Yong-Sheng], Lin, W.S.[Wei-Si],
Unified Information Fusion Network for Multi-Modal RGB-D and RGB-T Salient Object Detection,
CirSysVideo(32), No. 4, April 2022, pp. 2091-2106.
IEEE DOI 2204
Feature extraction, Task analysis, Visualization, Object detection, Image color analysis, Decoding, Bidirectional control, salient object detection BibRef

Zhang, Q.[Qiang], Duanmu, M.X.[Ming-Xing], Luo, Y.J.[Yong-Jiang], Liu, Y.[Yi], Han, J.G.[Jun-Gong],
Engaging Part-Whole Hierarchies and Contrast Cues for Salient Object Detection,
CirSysVideo(32), No. 6, June 2022, pp. 3644-3658.
IEEE DOI 2206
Object detection, Feature extraction, Routing, Noise measurement, Semantics, Saliency detection, Image segmentation, attention BibRef

Feng, G.[Guang], Meng, J.[Jinyu], Zhang, L.H.[Li-He], Lu, H.C.[Hu-Chuan],
Encoder Deep Interleaved Network with Multi-Scale Aggregation for RGB-D Salient Object Detection,
PR(128), 2022, pp. 108666.
Elsevier DOI 2205
RGB-D salient object detection, Deep interleaved encoder, Cross-modal mutual guidance, Real-time
See also Learning to Detect Salient Objects with Image-Level Supervision. BibRef

Zhou, J.Y.[Jia-Yuan], Wang, L.J.[Li-Jun], Lu, H.C.[Hu-Chuan], Huang, K.[Kaining], Shi, X.[Xinchu], Liu, B.[Bocong],
MVSalNet: Multi-view Augmentation for RGB-D Salient Object Detection,
ECCV22(XXIX:270-287).
Springer DOI 2211
BibRef

Pang, Y.W.[You-Wei], Zhao, X.Q.[Xiao-Qi], Zhang, L.H.[Li-He], Lu, H.C.[Hu-Chuan],
Multi-Scale Interactive Network for Salient Object Detection,
CVPR20(9410-9419)
IEEE DOI 2008
Feature extraction, Object detection, Aggregates, Spatial coherence, Training, Task analysis, Decoding BibRef

Wang, L.J.[Li-Jun], Lu, H.C.[Hu-Chuan], Wang, Y.F.[Yi-Fan], Feng, M.Y.[Meng-Yang], Wang, D.[Dong], Yin, B.C.[Bao-Cai], Ruan, X.[Xiang],
Learning to Detect Salient Objects with Image-Level Supervision,
CVPR17(3796-3805)
IEEE DOI 1711
Computational modeling, Detectors, Object detection, Semantics, Supervised learning, Training
See also Encoder Deep Interleaved Network with Multi-Scale Aggregation for RGB-D Salient Object Detection. BibRef

Zhang, H.S.[Hong-Shuang], Zeng, Y.[Yu], Lu, H.C.[Hu-Chuan], Zhang, L.[Lihe], Li, J.H.[Jian-Hua], Qi, J.Q.[Jin-Qing],
Learning to Detect Salient Object With Multi-Source Weak Supervision,
PAMI(44), No. 7, July 2022, pp. 3577-3589.
IEEE DOI 2206
Saliency detection, Annotations, Image segmentation, Dogs, Feature extraction, Task analysis, Noise measurement, Saliency, weak supervision BibRef

Wang, P.J.[Peng-Jie], Liu, Y.X.[Yu-Xuan], Cao, Y.[Ying], Yang, X.[Xin], Luo, Y.[Yu], Lu, H.C.[Hu-Chuan], Liang, Z.J.[Zi-Jian], Lau, R.W.H.[Rynson W.H.],
Salient object detection with image-level binary supervision,
PR(129), 2022, pp. 108782.
Elsevier DOI 2206
Weak supervision, Salient object detection, Binary labels
See also Encoder Deep Interleaved Network with Multi-Scale Aggregation for RGB-D Salient Object Detection. BibRef

Tian, X.[Xin], Xu, K.[Ke], Yang, X.[Xin], Yin, B.C.[Bao-Cai], Lau, R.W.H.[Rynson W. H.],
Learning to Detect Instance-Level Salient Objects Using Complementary Image Labels,
IJCV(130), No. 3, March 2022, pp. 729-746.
Springer DOI 2203
BibRef

Zhang, M.[Miao], Yao, S.Y.[Shun-Yu], Hu, B.Q.[Bei-Qi], Piao, Y.R.[Yong-Ri], Ji, W.[Wei],
C^2 DFNet: Criss-Cross Dynamic Filter Network for RGB-D Salient Object Detection,
MultMed(25), 2023, pp. 5142-5154.
IEEE DOI 2311
BibRef

Zhang, M.[Miao], Liu, J.[Jie], Wang, Y.F.[Yi-Fei], Piao, Y.R.[Yong-Ri], Yao, S.Y.[Shun-Yu], Ji, W.[Wei], Li, J.J.[Jing-Jing], Lu, H.C.[Hu-Chuan], Luo, Z.X.[Zhong-Xuan],
Dynamic Context-Sensitive Filtering Network for Video Salient Object Detection,
ICCV21(1533-1543)
IEEE DOI 2203
Convolution, Computational modeling, Object detection, Streaming media, Information filters, Real-time systems, Low-level and physics-based vision BibRef

Pang, Y.W.[You-Wei], Zhang, L.H.[Li-He], Zhao, X.Q.[Xiao-Qi], Lu, H.C.[Hu-Chuan],
Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection,
ECCV20(XXV:235-252).
Springer DOI 2011
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Qian, M.Y.[Ming-Yang], Qi, J.Q.[Jin-Qing], Zhang, L.[Lihe], Feng, M.Y.[Meng-Yang], Lu, H.C.[Hu-Chuan],
Language-aware weak supervision for salient object detection,
PR(96), 2019, pp. 106955.
Elsevier DOI 1909
Saliency detection, Natural language, Textual-visual pairwise, Self-supervision BibRef

Zhang, L.H.[Li-He], Sun, J.Y.[Jia-Yu], Wang, T.T.[Tian-Tian], Min, Y.F.[Yi-Fan], Lu, H.C.[Hu-Chuan],
Visual Saliency Detection via Kernelized Subspace Ranking With Active Learning,
IP(29), 2020, pp. 2258-2270.
IEEE DOI 2001
Saliency detection, Proposals, Visualization, Task analysis, Training, Uncertainty, Feature extraction, Saliency detection, feature projection BibRef

Wang, T.T.[Tian-Tian], Zhang, L.H.[Li-He], Lu, H.C.[Hu-Chuan], Sun, C.[Chong], Qi, J.Q.[Jin-Qing],
Kernelized Subspace Ranking for Saliency Detection,
ECCV16(VIII: 450-466).
Springer DOI 1611
BibRef

Zhang, P.P.[Ping-Ping], Wang, D.[Dong], Lu, H.C.[Hu-Chuan], Wang, H.Y.[Hong-Yu], Yin, B.,
Learning Uncertain Convolutional Features for Accurate Saliency Detection,
ICCV17(212-221)
IEEE DOI 1802
image segmentation, learning (artificial intelligence), neural nets, Uncertainty BibRef

Zhang, P.P.[Ping-Ping], Wang, D.[Dong], Lu, H.C.[Hu-Chuan], Wang, H.Y.[Hong-Yu], Ruan, X.[Xiang],
Amulet: Aggregating Multi-level Convolutional Features for Salient Object Detection,
ICCV17(202-211)
IEEE DOI 1802
convolution, data mining, feature extraction, image enhancement, image resolution, image segmentation, Visualization BibRef

Liu, Z.Y.[Zheng-Yi], Tan, Y.C.[Ya-Cheng], He, Q.[Qian], Xiao, Y.[Yun],
SwinNet: Swin Transformer Drives Edge-Aware RGB-D and RGB-T Salient Object Detection,
CirSysVideo(32), No. 7, July 2022, pp. 4486-4497.
IEEE DOI 2207
Transformers, Feature extraction, Task analysis, Decoding, Image edge detection, Object detection, multi-modality BibRef

Yang, Y.[Yang], Qin, Q.[Qi], Luo, Y.J.[Yong-Jiang], Liu, Y.[Yi], Zhang, Q.[Qiang], Han, J.G.[Jun-Gong],
Bi-Directional Progressive Guidance Network for RGB-D Salient Object Detection,
CirSysVideo(32), No. 8, August 2022, pp. 5346-5360.
IEEE DOI 2208
Feature extraction, Object detection, Saliency detection, Data mining, Bidirectional control, Task analysis, Visualization, bi-directional progressive guidance BibRef

Huang, K.[Kan], Tian, C.[Chunwei], Su, J.[Jingyong], Lin, J.C.W.[Jerry Chun-Wei],
Transformer-based Cross Reference Network for video salient object detection,
PRL(160), 2022, pp. 122-127.
Elsevier DOI 2208
Video salient: Object detection, Transformer, Cross-modal integration BibRef

Sun, P.[Peng], Zhang, W.H.[Wen-Hu], Li, S.Y.[Song-Yuan], Guo, Y.L.[Yi-Lin], Song, C.L.[Cong-Li], Li, X.[Xi],
Learnable Depth-Sensitive Attention for Deep RGB-D Saliency Detection with Multi-modal Fusion Architecture Search,
IJCV(130), No. 11, November 2022, pp. 2822-2841.
Springer DOI 2210
BibRef

Sun, P.[Peng], Zhang, W.H.[Wen-Hu], Wang, H.Y.[Huan-Yu], Li, S.Y.[Song-Yuan], Li, X.[Xi],
Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion,
CVPR21(1407-1417)
IEEE DOI 2111
Geometry, Visualization, Object detection, Benchmark testing, Pattern recognition BibRef

Ren, G.Y.[Guang-Yu], Xie, Y.C.[Yan-Chun], Dai, T.H.[Tian-Hong], Stathaki, T.[Tania],
Progressive multi-scale fusion network for RGB-D salient object detection,
CVIU(223), 2022, pp. 103529.
Elsevier DOI 2210
Multi-scale fusion, Mask guided, Salient object detection BibRef

Song, M.[Mengke], Song, W.F.[Wen-Feng], Yang, G.[Guowei], Chen, C.L.[Cheng-Lizhao],
Improving RGB-D Salient Object Detection via Modality-Aware Decoder,
IP(31), 2022, pp. 6124-6138.
IEEE DOI 2210
Decoding, Object detection, Training, Task analysis, Saliency detection, Image segmentation, Feature extraction, deep learning BibRef

Zhang, Q.D.[Qiu-Dan], Xiao, X.T.[Xiao-Tong], Wang, X.[Xu], Wang, S.Q.[Shi-Qi], Kwong, S.[Sam], Jiang, J.M.[Jian-Min],
Adaptive Viewpoint Feature Enhancement-Based Binocular Stereoscopic Image Saliency Detection,
CirSysVideo(32), No. 10, October 2022, pp. 6543-6556.
IEEE DOI 2210
Stereo image processing, Saliency detection, Feature extraction, Visualization, Neural networks, Image color analysis, binocular vision BibRef

Jin, X.[Xiao], Yi, K.[Kang], Xu, J.[Jing],
MoADNet: Mobile Asymmetric Dual-Stream Networks for Real-Time and Lightweight RGB-D Salient Object Detection,
CirSysVideo(32), No. 11, November 2022, pp. 7632-7645.
IEEE DOI 2211
Feature extraction, Object detection, Task analysis, Fuses, Saliency detection, Real-time systems, Decoding, RGB-D SOD, cross-modality fusion BibRef

Jia, X.Z.[Xing-Zhao], DongYe, C.L.[Chang-Lei], Peng, Y.J.[Yan-Jun],
SiaTrans: Siamese transformer network for RGB-D salient object detection with depth image classification,
IVC(127), 2022, pp. 104549.
Elsevier DOI 2211
Transformer, RGB-D salient object detection, Siamese network, Image classification BibRef

Xia, C.X.[Chen-Xing], Duan, S.S.[Song-Song], Gao, X.J.[Xiu-Ju], Sun, Y.G.[Yan-Guang], Huang, R.M.[Rong-Mei], Ge, B.[Bin],
GCENet: Global contextual exploration network for RGB-D salient object detection,
JVCIR(89), 2022, pp. 103680.
Elsevier DOI 2212
Salient object detection, Convolution neural network, Multi-scale, Global contextual BibRef

Wu, Y.H.[Yu-Huan], Liu, Y.[Yun], Xu, J.[Jun], Bian, J.W.[Jia-Wang], Gu, Y.C.[Yu-Chao], Cheng, M.M.[Ming-Ming],
MobileSal: Extremely Efficient RGB-D Salient Object Detection,
PAMI(44), No. 12, December 2022, pp. 10261-10269.
IEEE DOI 2212
Feature extraction, Image restoration, Fuses, Object detection, Streaming media, Convolution, Semantics, implicit depth restoration BibRef

Xu, Y.Q.[Yun-Qiu], Yu, X.[Xin], Zhang, J.[Jing], Zhu, L.C.[Lin-Chao], Wang, D.D.[Da-Dong],
Weakly Supervised RGB-D Salient Object Detection With Prediction Consistency Training and Active Scribble Boosting,
IP(31), 2022, pp. 2148-2161.
IEEE DOI 2203
Training, Image edge detection, Annotations, Feature extraction, Task analysis, Object detection, Data mining, weakly supervised learning BibRef

Zhao, W.[Wangbo], Zhang, J.[Jing], Li, L.[Long], Barnes, N.M.[Nick M.], Liu, N.[Nian], Han, J.W.[Jun-Wei],
Weakly Supervised Video Salient Object Detection,
CVPR21(16821-16830)
IEEE DOI 2111
Training, Annotations, Object detection, Boosting, Data models, Pattern recognition BibRef

Li, A.[Aixuan], Mao, Y.X.[Yu-Xin], Zhang, J.[Jing], Dai, Y.C.[Yu-Chao],
Mutual Information Regularization for Weakly-Supervised RGB-D Salient Object Detection,
CirSysVideo(34), No. 1, January 2024, pp. 397-410.
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhang, J.[Jing], Yu, X.[Xin], Li, A.X.[Ai-Xuan], Song, P.P.[Pei-Pei], Liu, B.[Bowen], Dai, Y.C.[Yu-Chao],
Weakly-Supervised Salient Object Detection via Scribble Annotations,
CVPR20(12543-12552)
IEEE DOI 2008
Object detection, Image edge detection, Semantics, Image segmentation, Training, Logic gates, Measurement BibRef

Zhao, X.Q.[Xiao-Qi], Pang, Y.W.[You-Wei], Zhang, L.[Lihe], Lu, H.C.[Hu-Chuan],
Joint Learning of Salient Object Detection, Depth Estimation and Contour Extraction,
IP(31), 2022, pp. 7350-7362.
IEEE DOI 2212
Task analysis, Transformers, Multitasking, Decoding, Object detection, Estimation, Feature extraction, modality-specific filters BibRef

Xia, C.X.[Cheng-Xing], Duan, S.S.[Song-Song], Ge, B.[Bin], Zhang, H.L.[Han-Ling], Li, K.C.[Kuan-Ching],
HDNet: Multi-Modality Hierarchy-Aware Decision Network for RGB-D Salient Object Detection,
SPLetters(29), 2022, pp. 2577-2581.
IEEE DOI 2301
Feature extraction, Image edge detection, Fuses, Object detection, Transformers, Frequency modulation, Cognition, salient object detection BibRef

Duan, S.S.[Song-Song], Xia, C.X.[Chen-Xing], Gao, X.J.[Xiu-Ju], Ge, B.[Bin], Zhang, H.L.[Han-Ling], Li, K.C.[Kuan-Ching],
Multi-Modality Diversity Fusion Network with Swintransformer for RGB-D Salient Object Detection,
ICIP22(1076-1080)
IEEE DOI 2211
Technological innovation, Object detection, Diversity methods, Benchmark testing, Decoding, Task analysis, diversity fusion BibRef

Bi, H.B.[Hong-Bo], Wu, R.W.[Ran-Wan], Liu, Z.Q.[Zi-Qi], Zhu, H.H.[Hui-Hui], Zhang, C.[Cong], Xiang, T.Z.[Tian-Zhu],
Cross-Modal Hierarchical Interaction Network for RGB-D Salient Object Detection,
PR(136), 2023, pp. 109194.
Elsevier DOI 2301
Saliency detection, Salient object detection, RGB-D, Feature fusion, Cross-modal interaction BibRef

Deng, J.Z.[Jing-Zheng], Zhang, J.X.[Jin-Xia], Hu, Z.[Zewen], Wang, L.[Liantao], Jiang, J.C.[Jia-Cheng], Zhu, X.C.[Xin-Chao], Chen, X.[Xinyi], Yuan, Y.[Yin], Wang, C.[Chao],
RGB-D salient object ranking based on depth stack and truth stack for complex indoor scenes,
PR(137), 2023, pp. 109251.
Elsevier DOI 2302
Complex scenes, RGB-D, Salient object ranking, Indoor, Depth BibRef

Li, J.J.[Jing-Jing], Ji, W.[Wei], Zhang, M.[Miao], Piao, Y.R.[Yong-Ri], Lu, H.C.[Hu-Chuan], Cheng, L.[Li],
Delving into Calibrated Depth for Accurate RGB-D Salient Object Detection,
IJCV(131), No. 1, January 2023, pp. 855-876.
Springer DOI 2303
BibRef

Zhu, L.[Lei], Wang, X.Q.[Xiao-Qiang], Li, P.[Ping], Yang, X.[Xin], Zhang, Q.[Qing], Wang, W.M.[Wei-Ming], Schönlieb, C.B.[Carola-Bibiane], Chen, C.L.P.[C. L. Philip],
S^3 Net: Self-Supervised Self-Ensembling Network for Semi-Supervised RGB-D Salient Object Detection,
MultMed(25), 2023, pp. 676-689.
IEEE DOI 2303
Saliency detection, Feature extraction, Convolutional neural networks, Task analysis, Detectors, and cross-model and cross-level feature aggregation BibRef

Wu, Z.W.[Zong-Wei], Allibert, G.[Guillaume], Meriaudeau, F.[Fabrice], Ma, C.[Chao], Demonceaux, C.[Cédric],
HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness,
IP(32), 2023, pp. 2160-2173.
IEEE DOI 2304
Feature extraction, Saliency detection, Decoding, Semantics, Object detection, Electromagnetic interference, Visualization, RGB-D saliency detection BibRef

Chen, G.[Gang], Shao, F.[Feng], Chai, X.L.[Xiong-Li], Chen, H.W.[Hang-Wei], Jiang, Q.P.[Qiu-Ping], Meng, X.C.[Xiang-Chao], Ho, Y.S.[Yo-Sung],
Modality-Induced Transfer-Fusion Network for RGB-D and RGB-T Salient Object Detection,
CirSysVideo(33), No. 4, April 2023, pp. 1787-1801.
IEEE DOI 2304
Semantics, Task analysis, Feature extraction, Fuses, Object detection, Image color analysis, transformer BibRef

Xie, Z.X.[Zheng-Xuan], Shao, F.[Feng], Chen, G.[Gang], Chen, H.W.[Hang-Wei], Jiang, Q.P.[Qiu-Ping], Meng, X.C.[Xiang-Chao], Ho, Y.S.[Yo-Sung],
Cross-Modality Double Bidirectional Interaction and Fusion Network for RGB-T Salient Object Detection,
CirSysVideo(33), No. 8, August 2023, pp. 4149-4163.
IEEE DOI 2308
Feature extraction, Object detection, Task analysis, Convolution, Fuses, Thermal sensors, Thermal noise, multi-modal fusion BibRef

Wang, Y.[Yue], Jia, X.[Xu], Zhang, L.[Lu], Li, Y.[Yuke], Elder, J.H.[James H.], Lu, H.C.[Hu-Chuan],
A uniform transformer-based structure for feature fusion and enhancement for RGB-D saliency detection,
PR(140), 2023, pp. 109516.
Elsevier DOI 2305
Saliency detection, RGB-D image, Transformer, Attention BibRef

Liu, C.[Chang], Yang, G.[Gang], Wang, S.[Shuo], Wang, H.X.[Hang-Xu], Zhang, Y.H.[Yun-Hua], Wang, Y.[Yutao],
TANet: Transformer-based asymmetric network for RGB-D salient object detection,
IET-CV(17), No. 4, 2023, pp. 415-430.
DOI Link 2306
image segmentation, object detection BibRef

Ling, L.Y.[Liu-Yi], Wang, Y.W.[Yi-Wen], Wang, C.J.[Cheng-Jun], Xu, S.Y.[Shan-Yong], Huang, Y.R.[You-Rui],
Depth-aware lightweight network for RGB-D salient object detection,
IET-IPR(17), No. 8, 2023, pp. 2350-2361.
DOI Link 2306
depth-aware, lightweight, RGB-D salient object detection BibRef

Li, X.[Xiang], Zhang, Q.[Qing], Yan, W.Q.[Wei-Qi], Dai, M.[Meng],
Depth Cue Enhancement and Guidance Network for RGB-D Salient Object Detection,
JVCIR(95), 2023, pp. 103880.
Elsevier DOI 2309
RGB-D salient object detection, Depth cue enhancement, Multi-modal feature fusion, Depth guidance BibRef

Sun, C.[Chao], Wu, X.[Xing], Sun, J.[Jia], Sun, C.Y.[Chang-Yin], Xu, M.Z.[Ming-Zhu], Ge, Q.B.[Quan-Bo],
Saliency-Induced Moving Object Detection for Robust RGB-D Vision Navigation Under Complex Dynamic Environments,
ITS(24), No. 10, October 2023, pp. 10716-10734.
IEEE DOI 2310
BibRef

Gao, H.[Huan], Guo, J.[Jichang], Wang, Y.D.[Yu-Dong], Dong, J.A.[Jian-An],
Dual attention guided multi-scale fusion network for RGB-D salient object detection,
SP:IC(118), 2023, pp. 117004.
Elsevier DOI 2310
RGB-D saliency object detection, Selective multi-scale fusion, Dual attention BibRef

Wei, W.Y.[Wei-Yi], Xu, M.Y.[Meng-Yu], Wang, J.[Jian], Luo, X.[Xuzhe],
Bidirectional Attentional Interaction Networks for RGB-D salient object detection,
IVC(138), 2023, pp. 104792.
Elsevier DOI 2310
RGB-D salient object detection, Cross-modality feature, Bidirectional interaction, Guidance aggregation BibRef

Cai, Z.[Ziyun], Jing, X.Y.[Xiao-Yuan], Shao, L.[Ling],
Domain embedding transfer for unequal RGB-D image recognition,
PR(143), 2023, pp. 109771.
Elsevier DOI 2310
Domain adaptation, RGB-D data, Visual categorization, Unequal category BibRef

Cheng, X.L.[Xiao-Long], Zheng, X.[Xuan], Pei, J.[Jialun], Tang, H.[He], Lyu, Z.[Zehua], Chen, C.B.[Chuan-Bo],
Depth-Induced Gap-Reducing Network for RGB-D Salient Object Detection: An Interaction, Guidance and Refinement Approach,
MultMed(25), 2023, pp. 4253-4266.
IEEE DOI 2310
BibRef

Meng, L.B.[Ling-Bing], Yuan, M.Y.[Meng-Ya], Shi, X.[Xuehan], Liu, Q.Q.[Qing-Qing], Cheng, F.[Fei], Li, L.L.[Ling-Li],
Three-stream RGB-D salient object detection network based on cross-level and cross-modal dual-attention fusion,
IET-IPR(17), No. 11, 2023, pp. 3292-3308.
DOI Link 2310
cross-modal fusion, depth map, dual-attention fusion, images, salient object detection, three-stream model BibRef

Liu, Z.[Zhiyu], Hayat, M.[Munawar], Yang, H.[Hong], Peng, D.[Duo], Lei, Y.J.[Yig-Jie],
Deep Hypersphere Feature Regularization for Weakly Supervised RGB-D Salient Object Detection,
IP(32), 2023, pp. 5423-5437.
IEEE DOI Code:
WWW Link. 2310
BibRef

Yao, S.Y.[Shun-Yu], Zhang, M.[Miao], Piao, Y.[Yongri], Qiu, C.Y.[Chao-Yi], Lu, H.C.[Hu-Chuan],
Depth Injection Framework for RGBD Salient Object Detection,
IP(32), 2023, pp. 5340-5352.
IEEE DOI 2310
BibRef

Zhang, Z.Y.[Zi-Yan], Gao, P.[Pan], Peng, S.[Siyi], Duan, C.[Chang], Zhang, P.[Ping],
Enhanced Point Feature Network for Point Cloud Salient Object Detection,
SPLetters(30), 2023, pp. 1617-1621.
IEEE DOI 2311
BibRef

Li, L.[Long], Han, J.W.[Jun-Wei], Liu, N.[Nian], Khan, S.[Salman], Cholakkal, H.[Hisham], Anwer, R.M.[Rao Muhammad], Khan, F.S.[Fahad Shahbaz],
Robust Perception and Precise Segmentation for Scribble-Supervised RGB-D Saliency Detection,
PAMI(46), No. 1, January 2024, pp. 479-496.
IEEE DOI 2312
BibRef

Gao, L.[Lina], Liu, B.[Bing], Fu, P.[Ping], Xu, M.Z.[Ming-Zhu],
TSVT: Token Sparsification Vision Transformer for robust RGB-D salient object detection,
PR(148), 2024, pp. 110190.
Elsevier DOI 2402
Salient object detection, RGB-D image, Self-attention mechanism, Vision transformer, Token sparsification BibRef

Chen, J.L.[Jian-Lin], Li, G.Y.[Gong-Yang], Zhang, Z.J.[Zhi-Jiang], Zeng, D.[Dan],
EFDCNet: Encoding Fusion and Decoding Correction Network for RGB-D Indoor Semantic Segmentation,
IVC(142), 2024, pp. 104892.
Elsevier DOI Code:
WWW Link. 2402
RGB-D indoor semantic segmentation, Encoding fusion, Decoding correction BibRef

Sun, F.[Fuming], Ren, P.[Peng], Yin, B.[Bowen], Wang, F.S.[Fa-Sheng], Li, H.J.[Hao-Jie],
CATNet: A Cascaded and Aggregated Transformer Network for RGB-D Salient Object Detection,
MultMed(26), 2024, pp. 2249-2262.
IEEE DOI 2402
Feature extraction, Transformers, Task analysis, Image edge detection, Object detection, Charge coupled devices, decoder BibRef

Xiao, F.[Fen], Pu, Z.D.[Zheng-Dong], Chen, J.Q.[Jia-Qi], Gao, X.P.[Xie-Ping],
DGFNet: Depth-Guided Cross-Modality Fusion Network for RGB-D Salient Object Detection,
MultMed(26), 2024, pp. 2648-2658.
IEEE DOI 2402
Feature extraction, Object detection, Fuses, Task analysis, Semantics, Data mining, Visualization, cross-modal feature fusion BibRef

Wu, J.S.[Jie-Sheng], Hao, F.W.[Fang-Wei], Liang, W.[Weiyun], Xu, J.[Jing],
Transformer Fusion and Pixel-Level Contrastive Learning for RGB-D Salient Object Detection,
MultMed(26), 2024, pp. 1011-1026.
IEEE DOI 2402
Transformers, Feature extraction, Task analysis, Object detection, Fuses, Computational complexity, Multi-modality fusion, transformer BibRef

Zhang, Q.[Qiang], Qin, Q.[Qi], Yang, Y.[Yang], Jiao, Q.[Qiang], Han, J.G.[Jun-Gong],
Feature Calibrating and Fusing Network for RGB-D Salient Object Detection,
CirSysVideo(34), No. 3, March 2024, pp. 1493-1507.
IEEE DOI 2403
Visualization, Object detection, Image synthesis, Feature extraction, Cognition, Saliency detection, Streaming media, region consistency aware loss BibRef

Zeng, Z.H.[Zhi-Hong], Liu, H.J.[Hai-Jun], Chen, F.L.[Feng-Lei], Tan, X.H.[Xiao-Heng],
AirSOD: A Lightweight Network for RGB-D Salient Object Detection,
CirSysVideo(34), No. 3, March 2024, pp. 1656-1669.
IEEE DOI 2403
Computational modeling, Feature extraction, Computational complexity, Atmospheric modeling, Streaming media, hybrid feature extraction network BibRef


Wang, Y.[Yang], Zhang, Y.Q.[Yan-Qing],
Three-stage Bidirectional Interaction Network for Efficient RGB-D Salient Object Detection,
ACCV22(V:215-233).
Springer DOI 2307
BibRef

Hu, M.J.[Ming-Jun], Zhang, X.Q.[Xiao-Qin], Zhao, L.[Li],
Multi-scale Residual Interaction for RGB-D Salient Object Detection,
ACCV22(III:575-590).
Springer DOI 2307
BibRef

Lee, M.[Minhyeok], Park, C.[Chaewon], Cho, S.[Suhwan], Lee, S.Y.[Sang-Youn],
SPSN: Superpixel Prototype Sampling Network for RGB-D Salient Object Detection,
ECCV22(XXIX:630-647).
Springer DOI 2211
BibRef

Fan, S.L.[Song-Lin], Gao, W.[Wei], Li, G.[Ge],
Salient Object Detection for Point Clouds,
ECCV22(XXVIII:1-19).
Springer DOI 2211
BibRef

Zhou, J.L.[Jin-Lin], Luo, Z.M.[Zhi-Ming], Li, S.Z.[Shao-Zi],
Dynamic Selection Network For Rgb-D Salient Object Detection,
ICIP22(776-780)
IEEE DOI 2211
Adaptation models, Cross layer design, Fuses, Computational modeling, Object detection, Decoding, RGB-D, skip connection BibRef

Song, P.P.[Pei-Pei], Zhang, J.[Jing], Koniusz, P.[Piotr], Barnes, N.M.[Nick M.],
Multi-Modal Transformer for RGB-D Salient Object Detection,
ICIP22(2466-2470)
IEEE DOI 2211
Correlation, Fuses, Object detection, Benchmark testing, Transformers, Data models, RGB-D Salient Object Detection, Multi-modal Fusion BibRef

Ying, X.W.[Xiao-Wen], Chuah, M.C.[Mooi Choo],
UCTNet: Uncertainty-Aware Cross-Modal Transformer Network for Indoor RGB-D Semantic Segmentation,
ECCV22(XXX:20-37).
Springer DOI 2211
BibRef

van Hoorick, B.[Basile], Tendulkar, P.[Purva], Surís, D.[Dídac], Park, D.[Dennis], Stent, S.[Simon], Vondrick, C.[Carl],
Revealing Occlusions with 4D Neural Fields,
CVPR22(3001-3011)
IEEE DOI 2210

WWW Link. Point cloud compression, Visualization, Computational modeling, Data visualization, Data models, Spatiotemporal phenomena, Deep learning architectures and techniques BibRef

Zhang, J.[Jing], Fan, D.P.[Deng-Ping], Dai, Y.C.[Yu-Chao], Yu, X.[Xin], Zhong, Y.[Yiran], Barnes, N.M.[Nick M.], Shao, L.[Ling],
RGB-D Saliency Detection via Cascaded Mutual Information Minimization,
ICCV21(4318-4327)
IEEE DOI 2203
Codes, Annotations, Computational modeling, Redundancy, Benchmark testing, Minimization, grouping and shape BibRef

Zhou, T.[Tao], Fu, H.Z.[Hua-Zhu], Chen, G.[Geng], Zhou, Y.[Yi], Fan, D.P.[Deng-Ping], Shao, L.[Ling],
Specificity-preserving RGB-D Saliency Detection,
ICCV21(4661-4671)
IEEE DOI 2203
Codes, Fuses, Computational modeling, Benchmark testing, Feature extraction, Light fields, BibRef

Wu, Z.W.[Zong-Wei], Allibert, G.[Guillaume], Stolz, C.[Christophe], Ma, C.[Chao], Demonceaux, C.[Cédric],
Modality-Guided Subnetwork for Salient Object Detection,
3DV21(515-524)
IEEE DOI 2201
Adaptation models, Solid modeling, Costs, Shape, Object detection, Transforms, RGBD Salient Object Detection, Cross Modal Fusion BibRef

Paigwar, A.[Anshul], Sierra-Gonzalez, D.[David], Erkent, Ö.[Özgür], Laugier, C.[Christian],
Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR,
AVVision21(2926-2933)
IEEE DOI 2112
Location awareness, Laser radar, Runtime, Object detection, Feature extraction, Cameras BibRef

Ji, W.[Wei], Li, J.J.[Jing-Jing], Yu, S.[Shuang], Zhang, M.[Miao], Piao, Y.[Yongri], Yao, S.[Shunyu], Bi, Q.[Qi], Ma, K.[Kai], Zheng, Y.F.[Ye-Feng], Lu, H.C.[Hu-Chuan], Cheng, L.[Li],
Calibrated RGB-D Salient Object Detection,
CVPR21(9466-9476)
IEEE DOI 2111
Codes, Fuses, Computational modeling, Object detection, Boosting, Calibration BibRef

Zhang, B.[Bin], Kang, X.J.[Xue-Jing], Ming, A.[Anlong],
BP-net: deep learning-based superpixel segmentation for RGB-D image,
ICPR21(7433-7438)
IEEE DOI 2105
Geometry, Image segmentation, Shape, Image edge detection, Neural networks, Filtering algorithms, Feature extraction BibRef

Wang, X.Q.[Xue-Qing], Hou, Y.L.[Ya-Li], Hao, X.L.[Xiao-Li], Shen, Y.[Yan], Liu, S.[Shuai],
Automatic 3d Object Detection from RGB-D Data Using PU-GAN,
ISVC20(II:742-752).
Springer DOI 2103
BibRef

Zhao, X.Q.[Xiao-Qi], Zhang, L.H.[Li-He], Pang, Y.W.[You-Wei], Lu, H.C.[Hu-Chuan], Zhang, L.[Lei],
A Single Stream Network for Robust and Real-time RGB-D Salient Object Detection,
ECCV20(XXII:646-662).
Springer DOI 2011
BibRef

Chen, S.H.[Shu-Han], Fu, Y.[Yun],
Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection,
ECCV20(VIII:520-538).
Springer DOI 2011
BibRef

Zhang, M.[Miao], Fei, S.X.[Sun Xiao], Liu, J.[Jie], Xu, S.[Shuang], Piao, Y.[Yongri], Lu, H.C.[Hu-Chuan],
Asymmetric Two-stream Architecture for Accurate RGB-D Saliency Detection,
ECCV20(XXVIII:374-390).
Springer DOI 2011
BibRef

Zhao, J.X.[Jia-Xing], Cao, Y.[Yang], Fan, D.P.[Deng-Ping], Cheng, M.M.[Ming-Ming], Li, X.Y.[Xuan-Yi], Zhang, L.[Le],
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection,
CVPR19(3922-3931).
IEEE DOI 2002
BibRef

Wang, S.T.[Song-Tao], Zhou, Z.[Zhen], Qu, H.B.[Han-Bing], Li, B.[Bin],
RGB-D saliency detection under Bayesian framework,
ICPR16(1881-1886)
IEEE DOI 1705
Computational modeling, Feature extraction, Image color analysis, Solid modeling, Visualization BibRef

Yun, J.S., Sim, J.Y.,
Supervoxel-based saliency detection for large-scale colored 3D point clouds,
ICIP16(4062-4066)
IEEE DOI 1610
Clustering algorithms BibRef

Dabala, L.[Lukasz], Rokita, P.[Przemyslaw],
Depth Guided Detection of Salient Objects,
ICCVG16(197-205).
Springer DOI 1611
BibRef

Mukherjee, S., Cheng, I., Basu, A.,
Highlighting objects of interest in an image by integrating saliency and depth,
ICIP16(6-10)
IEEE DOI 1610
Adaptation models BibRef

Xue, H.Y.[Hao-Yang], Gu, Y.[Yun], Li, Y.J.[Yi-Jun], Yang, J.[Jie],
RGB-D saliency detection via mutual guided manifold ranking,
ICIP15(666-670)
IEEE DOI 1512
Depth map cues; Mutual guided manifold ranking; Saliency detection BibRef

Ren, J.Q.[Jian-Qiang], Gong, X.J.[Xiao-Jin], Yu, L.[Lu], Zhou, W.H.[Wen-Hui], Yang, M.Y.[Michael Ying],
Exploiting global priors for RGB-D saliency detection,
FusionDynamic15(25-32)
IEEE DOI 1510
Image color analysis BibRef

Chapter on 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing continues in
Point Cloud Processing for Neural Networks, Convolutional Neural Networks .


Last update:Mar 16, 2024 at 20:36:19