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
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
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
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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
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Depth incorporating with color improves salient object detection,
VC(32), No. 1, January 2016, pp. 111-121.
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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],
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Retracted: An iterative propagation based co-saliency framework for RGBD images,
JVCIR(77), 2021, pp. 103083.
Elsevier DOI
2106
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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],
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IEICE(E102-D), No. 3, March 2019, pp. 688-689.
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Ding, Y.[Yu],
Liu, Z.[Zhi],
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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],
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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.
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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],
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IVC(101), 2020, pp. 103964.
Elsevier DOI
2009
RGBD, Saliency, Cross-modal, Feature extraction, Integration
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Luo, A.[Ao],
Li, X.[Xin],
Yang, F.[Fan],
Jiao, Z.C.[Zhi-Cheng],
Cheng, H.[Hong],
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Cascade Graph Neural Networks for RGB-D Salient Object Detection,
ECCV20(XII: 346-364).
Springer DOI
2010
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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],
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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
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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
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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
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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
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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],
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
BibRef
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.[Nick],
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
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.[Yunhua],
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
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.[Nick],
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.[Nick],
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
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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
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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 .