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
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.[Ruofeng],
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.[Yuqiu],
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
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.[Guangyu],
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. Pages855-876.
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
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
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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,
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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
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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
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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
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ECCV20(XXVIII:374-390).
Springer DOI
2011
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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
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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
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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 .