7.1.10.1 Salient Regions, Saliencey for Regions

Liu, Q., Hong, X., Zou, B., Chen, J., Chen, Z., Zhao, G.,
Hierarchical Contour Closure-Based Holistic Salient Object Detection,
IP(26), No. 9, September 2017, pp. 4537-4552.
IEEE DOI 1708
image segmentation, object detection, background saliency overestimation, closure completeness, closure reliability, fine-grained contrast-based salient object detection, hierarchical contour closure-based holistic salient object detection, hierarchical segmentation space, holistic homogeneous regions, saliency cues, saliency maps, salient object saliency attenuation, Attenuation, Image segmentation, Object detection, Object segmentation, Psychology, Reliability, Salient object detection, closure completeness, closure reliability, contour, closure BibRef

Yan, X.Y.[Xiao-Yun], Wang, Y.H.[Yue-Huan], Song, Q.[Qiong], Dai, K.H.[Kai-Heng],
Salient object detection via boosting object-level distinctiveness and saliency refinement,
JVCIR(48), No. 1, 2017, pp. 224-237.
Elsevier DOI 1708
BibRef
Earlier:
Salient object detection by multi-level features learning determined sparse reconstruction,
ICIP16(2762-2766)
IEEE DOI 1610
Saliency. Feature extraction BibRef

Li, R.H.[Rui-Hui], Cai, J.R.[Jian-Rui], Zhang, H.L.[Han-Ling], Wang, T.H.[Tai-Hong],
Aggregating complementary boundary contrast with smoothing for salient region detection,
VC(33), No. 9, September 2017, pp. 1155-1167.
WWW Link. 1708
BibRef

Lin, H.F.[Hua-Feng], Li, J.[Jing], Zhou, P.Y.[Pei-Yun], Liang, D.C.[Da-Chuan], Li, D.M.[Dong-Min],
Saliency detection using adaptive background template,
IET-CV(11), No. 6, September 2017, pp. 389-397.
DOI Link 1709
BibRef

Yang, C., Pu, J., Xie, G.S., Dong, Y., Liu, Z.,
Extended Locality-Constrained Linear Self-Coding for Saliency Detection,
SPLetters(24), No. 10, October 2017, pp. 1458-1462.
IEEE DOI 1710
linear codes, object detection, feature distance, foreground saliency, BibRef

Yang, C.L.[Chun-Lei], Pu, J.[Jiexin], Dong, Y.S.[Yong-Sheng], Liu, Z.H.[Zhong-Hua], Liang, L.F.[Ling-Fei], Wang, X.H.[Xiao-Hong],
Salient object detection in complex scenes via D-S evidence theory based region classification,
VC(33), No. 11, November 2017, pp. 1415-1428.
Springer DOI 1710
BibRef

Oh, J.[Jongsuk], Kim, H.I.[Hong-In], Park, R.H.[Rae-Hong],
Context-based abnormal object detection using the fully-connected conditional random fields,
PRL(98), No. 1, 2017, pp. 16-25.
Elsevier DOI 1710
Abnormal object detection BibRef

Yang, Z.[Zhen], Xiong, H.L.[Hui-Lin],
Computing object-based saliency via locality-constrained linear coding and conditional random fields,
VC(33), No. 11, November 2017, pp. 1403-1413.
Springer DOI 1710
BibRef

Li, Z.[Zun], Lang, C.Y.[Cong-Yan], Feng, S.H.[Song-He], Wang, T.[Tao],
Saliency ranker: A new salient object detection method,
JVCIR(50), No. 1, 2018, pp. 16-26.
Elsevier DOI 1712
Saliency detection BibRef

Liang, J.[Jie], Zhou, J.[Jun], Tong, L.[Lei], Bai, X.[Xiao], Wang, B.[Bin],
Material based salient object detection from hyperspectral images,
PR(76), No. 1, 2018, pp. 476-490.
Elsevier DOI 1801
Salient object detection BibRef

Al-Khafaji, S.L.[Suhad Lateef], Zhou, J.[Jun], Liew, A.W.C.[Alan Wee-Chung],
An Efficient Method for Boundary Detection from Hyperspectral Imagery,
SSSPR18(416-426).
Springer DOI 1810
BibRef

Al-Khafaji, S.L.[Suhad Lateef], Zia, A.[Ali], Zhou, J.[Jun], Liew, A.W.C.[Alan Wee-Chung],
Material Based Boundary Detection in Hyperspectral Images,
DICTA17(1-7)
IEEE DOI 1804
feature extraction, geophysical image processing, hyperspectral imaging, matrix algebra, pattern clustering, Probability density function BibRef

Li, X.[Xi], Ma, H.M.[Hui-Min], Wang, X.[Xiang], Zhang, K.[Kai],
Saliency detection via alternative optimization adaptive influence matrix model,
PRL(101), No. 1, 2018, pp. 29-36.
Elsevier DOI 1801
Salient object detection BibRef

Yi, L.[Liu], Qiang, Z.[Zhang], Jungong, H.[Han], Long, W.[Wang],
Salient object detection employing robust sparse representation and local consistency,
IVC(69), 2018, pp. 155-167.
Elsevier DOI 1802
Salient object detection, Robust sparse representation, Local consistency, Complex structures BibRef

Eun, H.J.[Hyun-Jun], Kim, Y.[Yoonhyung], Jung, C.[Chanho], Kim, C.[Changick],
Saliency refinement: Towards a uniformly highlighted salient object,
SP:IC(62), 2018, pp. 16-32.
Elsevier DOI 1802
Salient object detection, Saliency refinement, A uniformly highlighted salient object, Nonlocal optimization BibRef

Li, Y.[Ying], Cui, F.[Fan], Xue, X.[Xizhe], Chan, J.C.W.[Jonathan Cheung-Wai],
Coarse-to-fine salient object detection based on deep convolutional neural networks,
SP:IC(64), 2018, pp. 21-32.
Elsevier DOI 1804
Saliency detection, Convolutional neural network, Fully convolutional neural network BibRef

Wang, B.Y.[Bao-Yan], Zhang, T.[Tie], Wang, X.G.[Xin-Gang],
Salient object detection based on Laplacian similarity metrics,
VC(34), No. 5, May 2018, pp. 645-658.
WWW Link. 1804
BibRef

Quan, R., Han, J., Zhang, D., Nie, F., Qian, X., Li, X.,
Unsupervised Salient Object Detection via Inferring From Imperfect Saliency Models,
MultMed(20), No. 5, May 2018, pp. 1101-1112.
IEEE DOI 1805
Analytical models, Computational complexity, Computational modeling, Fuses, Labeling, Object detection, weak prediction BibRef

Zhang, Y.J.[Yong-Jun], Wang, X.[Xiang], Xie, X.W.[Xun-Wei], Li, Y.S.[Yan-Sheng],
Salient Object Detection via Recursive Sparse Representation,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
The foreground object. BibRef

Zhang, J.H.[Jian-Hua], Zhao, Y.Z.[Yan-Zhu], Chen, S.Y.[Sheng-Yong],
Object-level saliency: Fusing objectness estimation and saliency detection into a uniform framework,
JVCIR(53), 2018, pp. 102-112.
Elsevier DOI 1805
Object-level, Salient object detection, Saliency, Objectness, Background prior, Peeling BibRef

Nouri, F.[Fatemeh], Kazemi, K.[Kamran], Danyali, H.[Habibollah],
Salient object detection using local, global and high contrast graphs,
SIViP(12), No. 4, May 2018, pp. 659-667.
WWW Link. 1805
BibRef

Umeki, Y.[Yo], Yoshida, T.[Taichi], Iwahashi, M.[Masahiro],
Co-Propagation with Distributed Seeds for Salient Object Detection,
IEICE(E101-D), No. 6, June 2018, pp. 1640-1647.
WWW Link. 1806
BibRef

Dai, B.[Bo], Ye, W.J.[Wei-Jing], Zheng, J.[Jing], Chai, Q.Y.[Qian-Yi], Yao, Y.Y.[Yi-Yang],
Retraction: Deep network for visual saliency prediction by encoding image composition,
JVCIR(67), 2020, pp. 102756.
Elsevier DOI 2004
BibRef
Earlier: JVCIR(55), 2018, pp. 789-794.
Elsevier DOI 1809
Deep network, Visual saliency regions, Image composition BibRef

El Sayed, A.R.[Abdul Rahman], El Chakik, A.[Abdallah], Alabboud, H.[Hassan], Yassine, A.[Adnan],
Efficient 3D mesh salient region detection using local homogeneity measure,
IET-IPR(12), No. 9, September 2018, pp. 1663-1672.
DOI Link 1809
BibRef

Wang, Y.Z.[Yan-Zhao], Peng, G.H.[Guo-Hua],
Salient object detection based on compactness and foreground connectivity,
MVA(29), No. 7, October 2018, pp. 1143-1155.
WWW Link. 1810
BibRef

Yang, C.L.[Chun-Lei], Wang, X.L.[Xiang-Luo], Pu, J.X.[Jie-Xin], Xie, G.S.[Guo-Sen], Liu, Z.H.[Zhong-Hua], Dong, Y.S.[Yong-Sheng], Liang, L.F.[Ling-Fei],
Hybrid of extended locality-constrained linear coding and manifold ranking for salient object detection,
JVCIR(56), 2018, pp. 27-37.
Elsevier DOI 1811
Salient object detection, Complex scene, Locality-constrained Linear Coding (LLC), Manifold ranking, Region clustering BibRef

Xiao, H., Feng, J., Wei, Y., Zhang, M., Yan, S.,
Deep Salient Object Detection With Dense Connections and Distraction Diagnosis,
MultMed(20), No. 12, December 2018, pp. 3239-3251.
IEEE DOI 1812
learning (artificial intelligence), neural nets, object detection, distraction-free image, combined S-Net, model interpretability BibRef

Abkenar, M.R.[Masoumeh Rezaei], Sadreazami, H.[Hamidreza], Ahmad, M.O.[M. Omair],
Salient region detection using feature extraction in the non-subsampled contourlet domain,
IET-IPR(12), No. 12, December 2018, pp. 2275-2282.
DOI Link 1812
BibRef

Kampffmeyer, M.[Michael], Dong, N.Q.[Nan-Qing], Liang, X.D.[Xiao-Dan], Zhang, Y.[Yujia], Xing, E.P.[Eric P.],
ConnNet: A Long-Range Relation-Aware Pixel-Connectivity Network for Salient Segmentation,
IP(28), No. 5, May 2019, pp. 2518-2529.
IEEE DOI 1903
computer vision, convolutional neural nets, graph theory, image segmentation, inference mechanisms, probability, ConnNet, connectivity BibRef

Zhang, Q.[Qing], Lin, J.J.[Jia-Jun], Zhuge, J.J.[Jing-Jing], Yuan, W.H.[Wen-Hao],
Multi-level and multi-scale deep saliency network for salient object detection,
JVCIR(59), 2019, pp. 415-424.
Elsevier DOI 1903
Saliency detection, Salient object detection, Fully convolutional neural network, Multi-scale features BibRef

Nguyen, K.D.[Khanh-Duy], Nguyen, K.[Khang], Le, D.D.[Duy-Dinh], Duong, D.A.[Duc Anh], Nguyen, T.V.[Tam V.],
You always look again: Learning to detect the unseen objects,
JVCIR(60), 2019, pp. 206-216.
Elsevier DOI 1903
Deep learning, Dual-level deep networks, Object detection BibRef

Zhang, Q.A.[Qi-Ang], Huo, Z.[Zhen], Liu, Y.[Yi], Pan, Y.H.[Yun-Hui], Shan, C.F.[Cai-Feng], Han, J.G.[Jun-Gong],
Salient object detection employing a local tree-structured low-rank representation and foreground consistency,
PR(92), 2019, pp. 119-134.
Elsevier DOI 1905
Salient object detection, Structured low-rank representation, Background dictionary, Foreground consistency BibRef

Wang, Y., Zhao, X., Hu, X., Li, Y., Huang, K.,
Focal Boundary Guided Salient Object Detection,
IP(28), No. 6, June 2019, pp. 2813-2824.
IEEE DOI 1905
feature extraction, image segmentation, learning (artificial intelligence), object detection, deep learning BibRef

Zhang, P., Liu, W., Lu, H., Shen, C.,
Salient Object Detection With Lossless Feature Reflection and Weighted Structural Loss,
IP(28), No. 6, June 2019, pp. 3048-3060.
IEEE DOI 1905
computer vision, feature extraction, image classification, image segmentation, learning (artificial intelligence), spatially consistent saliency BibRef

Tao, Q.Y.[Qing-Yi], Yang, H.[Hao], Cai, J.F.[Jian-Fei],
Exploiting Web Images for Weakly Supervised Object Detection,
MultMed(21), No. 5, May 2019, pp. 1135-1146.
IEEE DOI 1905
convolutional neural nets, Internet, learning (artificial intelligence), object detection, curriculum learning BibRef

Jerripothula, K.R.[Koteswar Rao], Cai, J.F.[Jian-Fei], Yuan, J.S.[Jun-Song],
QCCE: Quality constrained co-saliency estimation for common object detection,
VCIP15(1-4)
IEEE DOI 1605
Estimation BibRef

Li, C.P.[Cui-Ping], Chen, Z.X.[Zhen-Xue], Wu, Q.M.J.[Q. M. Jonathan], Liu, C.Y.[Cheng-Yun],
Saliency object detection: integrating reconstruction and prior,
MVA(30), No. 3, April 2019, pp. 397-406.
Springer DOI 1906
BibRef

Li, H.Z.[Hong-Zhi], Ellis, J.G.[Joseph G.], Zhang, L.[Lei], Chang, S.F.[Shih-Fu],
Automatic visual pattern mining from categorical image dataset,
MultInfoRetr(8), No. 1, March 2019, pp. 35-45.
Springer DOI 1906
BibRef

Zhang, P.P.[Ping-Ping], Liu, W.[Wei], Lei, Y.[Yinjie], Lu, H.C.[Hu-Chuan],
Hyperfusion-Net: Hyper-densely reflective feature fusion for salient object detection,
PR(93), 2019, pp. 521-533.
Elsevier DOI 1906
Salient object detection, Image reflection separation, Multiple feature fusion, Convolutional Neural Network BibRef

Lin, X., Wang, Z., Ma, L., Wu, X.,
Saliency Detection via Multi-Scale Global Cues,
MultMed(21), No. 7, July 2019, pp. 1646-1659.
IEEE DOI 1906
Image segmentation, Saliency detection, Image resolution, Smoothing methods, Streaming media, Feature extraction, Proposals, image smoothing and segmentation BibRef

Xu, Q.Z.[Qing-Zhen], Wang, F.Y.[Feng-Yun], Gong, Y.Y.[Yong-Yi], Wang, Z.T.[Zhou-Tao], Zeng, K.[Kun], Li, Q.[Qi], Luo, X.N.[Xiao-Nan],
A novel edge-oriented framework for saliency detection enhancement,
IVC(87), 2019, pp. 1-12.
Elsevier DOI 1906
Saliency detection enhancements, Visual attention, Edge probability map, Edge-region BibRef

Singh, S.K.[Surya Kant], Srivastava, R.[Rajeev],
A Novel Probabilistic Contrast-Based Complex Salient Object Detection,
JMIV(61), No. 7, September 2019, pp. 990-1006.
WWW Link. 1908
BibRef

Tang, Y.B.[You-Bao], Wu, X.Q.[Xiang-Qian],
Salient Object Detection Using Cascaded Convolutional Neural Networks and Adversarial Learning,
MultMed(21), No. 9, September 2019, pp. 2237-2247.
IEEE DOI 1909
Object detection, Feature extraction, Generators, Estimation, Convolutional neural networks, Decoding, Kernel, adversarial learning BibRef

Chen, W.B.[Wen-Bing], Dahal, K.[Keshav], Huang, S.[Shuxian],
Salient object detection via reciprocal function filter,
IET-IPR(13), No. 10, 22 August 2019, pp. 1616-1624.
DOI Link 1909
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

Li, C.Y.[Chong-Yi], Cong, R.M.[Run-Min], Hou, J.H.[Jun-Hui], Zhang, S.Y.[San-Yi], Qian, Y.[Yue], Kwong, S.[Sam],
Nested Network With Two-Stream Pyramid for Salient Object Detection in Optical Remote Sensing Images,
GeoRS(57), No. 11, November 2019, pp. 9156-9166.
IEEE DOI 1911
Object detection, Optical imaging, Saliency detection, Optical sensors, Feature extraction, Optical network units, two-stream pyramid module BibRef

Zhang, Q.J.[Qi-Jian], Cong, R.M.[Run-Min], Li, C.Y.[Chong-Yi], Cheng, M.M.[Ming-Ming], Fang, Y.M.[Yu-Ming], Cao, X.C.[Xiao-Chun], Zhao, Y.[Yao], Kwong, S.[Sam],
Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images,
IP(30), 2021, pp. 1305-1317.
IEEE DOI 2012
Optical imaging, Optical sensors, Feature extraction, Visualization, Remote sensing, Task analysis, Object detection, optical remote sensing images BibRef

Nasiripour, R.[Reza], Farsi, H.[Hassan], Mohamadzadeh, S.[Sajad],
Visual saliency object detection using sparse learning,
IET-IPR(13), No. 13, November 2019, pp. 2436-2447.
DOI Link 1911
BibRef

Lu, Y.[Ye], Zhou, K.D.[Ke-Dong], Wu, X.Y.[Xi-Yin], Gong, P.H.[Peng-Han],
A novel multi-graph framework for salient object detection,
VC(35), No. 11, November 2018, pp. 1683-1699.
WWW Link. 1911
BibRef

Wang, Y.Z.[Yan-Zhao], Peng, G.H.[Guo-Hua],
Salient object detection via incorporating multiple manifold ranking,
SIViP(13), No. 8, November 2019, pp. 1603-1610.
WWW Link. 1911
BibRef

Zhou, D.F.[Ding-Fu], Fang, J.[Jin], Song, X.B.[Xi-Bin], Guan, C.Y.[Chen-Ye], Yin, J.B.[Jun-Bo], Dai, Y.C.[Yu-Chao], Yang, R.G.[Rui-Gang],
IoU Loss for 2D/3D Object Detection,
3DV19(85-94)
IEEE DOI 1911
Intersection-over-Union. Object detection, Task analysis, Measurement, Autonomous Driving BibRef

Wang, Z.J.[Zhi-Jie], Zhang, W.[Wei], Rong, X.[Xuewen], Li, Y.[Yibin],
Salient object detection with adversarial training,
IET-IPR(13), No. 14, 12 December 2019, pp. 2859-2865.
DOI Link 1912
BibRef

Pang, Y.[Yu], Yu, X.S.[Xiao-Sheng], Wang, Y.[Ying], Wu, C.D.[Cheng-Dong],
Salient object detection based on novel graph model,
JVCIR(65), 2019, pp. 102676.
Elsevier DOI 1912
Salient object detection, Background prior, Novel graph model, Saliency propagation, Optimization method BibRef

Ma, G., Chen, C., Li, S., Peng, C., Hao, A., Qin, H.,
Salient Object Detection via Multiple Instance Joint Re-Learning,
MultMed(22), No. 2, February 2020, pp. 324-336.
IEEE DOI 2001
Feature extraction, Object detection, Saliency detection, Visualization, Deep learning, Correlation, Topology, Joint Re-Learning BibRef

Cao, Y.P.[Yan-Peng], Fu, G.Z.[Gui-Zhong], Yang, J.X.[Jiang-Xin], Cao, Y.L.[Yan-Long], Yang, M.Y.[Michael Ying],
Accurate Salient Object Detection via Dense Recurrent Connections and Residual-Based Hierarchical Feature Integration,
SP:IC(78), 2019, pp. 103-112.
Elsevier DOI 1909
Convolutional neural network, Recurrent convolutional layer, Salient object detection, Hierarchical feature fusion, Deep supervision BibRef

Yang, J.X.[Jia-Xing], Fang, X.[Xiang], Zhang, L.[Lihe], Lu, H.C.[Hu-Chuan], Wei, G.H.[Guo-Hua],
Salient Object Detection via Double Random Walks with Dual Restarts,
IVC(93), 2020, pp. 103822.
Elsevier DOI 2001
Salient object detection, Double random walks, Propagation distance, Dual restarts BibRef

Sikha, O.K., Soman, K.P.,
Multi-resolution dynamic mode decomposition-based salient region detection in noisy images,
SIViP(14), No. 1, February 2020, pp. 167-175.
WWW Link. 2001
BibRef

Chen, S.[Shuhan], Tan, X.L.[Xiu-Li], Wang, B.[Ben], Lu, H., Hu, X.L.[Xue-Long], Fu, Y.,
Reverse Attention-Based Residual Network for Salient Object Detection,
IP(29), 2020, pp. 3763-3776.
IEEE DOI 2002
BibRef
Earlier: A1, A2, A3, A5, Only:
Reverse Attention for Salient Object Detection,
ECCV18(IX: 236-252).
Springer DOI 1810
Salient object detection, reverse attention, side-output residual learning, saliency prior BibRef

Wang, B.[Ben], Chen, S.H.[Shu-Han], Wang, J.[Jian], Hu, X.L.[Xue-Long],
Residual feature pyramid networks for salient object detection,
VC(36), No. 9, September 2020, pp. 1897-1908.
WWW Link. 2008
BibRef

Zhang, L., Wu, J., Wang, T., Borji, A., Wei, G., Lu, H.,
A Multistage Refinement Network for Salient Object Detection,
IP(29), 2020, pp. 3534-3545.
IEEE DOI 2002
Salient object detection, stagewise refinement, pyramid pooling module, layerwise recurrent, channel attention, global average pooling BibRef

Chen, J.H.[Jun-Hao], Niu, Y.Z.[Yu-Zhe], Wu, J.B.[Jian-Bin], Chen, J.R.[Jun-Rong],
Optimisation for image salient object detection based on semantic-aware clustering and CRF,
IET-CV(14), No. 2, March 2020, pp. 49-58.
DOI Link 2002
BibRef

Xu, C.[Cheng], Han, W.[Wei], Wang, D.Z.[Dong-Zhen], Huang, D.Q.[Da-Qing],
Salient Region Detection with Multi-Feature Fusion and Edge Constraint,
IEICE(E103-D), No. 4, April 2020, pp. 910-913.
WWW Link. 2004
BibRef

Luo, R.H.[Rong-Hua], Huang, H.L.[Huai-Lin], Wu, W.Z.[Wei-Zeng],
Salient object detection based on backbone enhanced network,
IVC(95), 2020, pp. 103876.
Elsevier DOI 2004
Salient object detection, Deep learning, Backbone network, Over-fitting BibRef

Srivastava, G.[Gargi], Srivastava, R.[Rajeev],
User-interactive salient object detection using YOLOv2, lazy snapping, and gabor filters,
MVA(31), No. 3, March 2020, pp. Article17.
WWW Link. 2004
BibRef

Liu, Z.Y.[Zheng-Yi], Tang, J.T.[Ji-Ting], Zhao, P.[Peng],
Salient object detection via hybrid upsampling and hybrid loss computing,
VC(36), No. 4, April 2020, pp. 843-853.
Springer DOI 2004
BibRef

Luo, A.[Ao], Li, X.[Xin], Yang, F.[Fan], Jiao, Z.C.[Zhi-Cheng], Cheng, H.[Hong],
Webly-supervised learning for salient object detection,
PR(103), 2020, pp. 107308.
Elsevier DOI 2005
Salient object detection, Webly-supervised learning, Deep learning BibRef

Zhang, M., Ji, W., Piao, Y., Li, J., Zhang, Y., Xu, S., Lu, H.,
LFNet: Light Field Fusion Network for Salient Object Detection,
IP(29), 2020, pp. 6276-6287.
IEEE DOI 2005
Light field, salient object detection, convolutional neural networks, fusion network BibRef

Li, C.Y.[Cheng-Yuan], Luo, B.[Bin], Hong, H.[Hailong], Su, X.[Xin], Wang, Y.[Yajun], Liu, J.[Jun], Wang, C.[Chenjie], Zhang, J.[Jing], Wei, L.[Linhai],
Object Detection Based on Global-Local Saliency Constraint in Aerial Images,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Greenberg, S.[Shlomo], Bensimon, M.[Moshe], Podeneshko, Y.[Yevgeny], Gens, A.[Alon],
Fusion of visual salience maps for object acquisition,
IET-CV(14), No. 4, June 2020, pp. 113-121.
DOI Link 2005
BibRef

Singh, V.K.[Vivek Kumar], Kumar, N.[Nitin],
Saliency bagging: a novel framework for robust salient object detection,
VC(36), No. 7, July 2020, pp. 1423-1441.
WWW Link. 2005
BibRef

Qin, X.B.[Xue-Bin], Zhang, Z.C.[Zi-Chen], Huang, C.Y.[Chen-Yang], Dehghan, M.[Masood], Zaiane, O.R.[Osmar R.], Jagersand, M.[Martin],
U2-Net: Going deeper with nested U-structure for salient object detection,
PR(106), 2020, pp. 107404.
Elsevier DOI 2006
Salient object detection, Convolutional neural network, Network architecture design, Nested U-structure, Multi-scale feature extraction BibRef

Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Dong, X.P.[Xing-Ping], Borji, A.[Ali], Yang, R.G.[Rui-Gang],
Inferring Salient Objects from Human Fixations,
PAMI(42), No. 8, August 2020, pp. 1913-1927.
IEEE DOI 2007
BibRef
Earlier: A1, A2, A3, A4, Only:
Salient Object Detection Driven by Fixation Prediction,
CVPR18(1711-1720)
IEEE DOI 1812
Visualization, Object detection, Task analysis, Predictive models, Deep learning, Biological system modeling, Measurement. Analytical models, Computational modeling, Predictive models BibRef

Mukherjee, P.[Prerana], Lall, B.[Brejesh],
Conditional Random Field based salient proposal set generation and its application in content aware seam carving,
SP:IC(87), 2020, pp. 115890.
Elsevier DOI 2007
object edge density. Structured prediction, Edge classification, Salient edge density based scoring, Salient region preserving seam carving BibRef

Yildirim, G.[Gökhan], Sen, D.[Debashis], Kankanhalli, M.[Mohan], Süsstrunk, S.[Sabine],
Evaluating salient object detection in natural images with multiple objects having multi-level saliency,
IET-IPR(14), No. 10, August 2020, pp. 2249-2262.
DOI Link 2008
BibRef

Liu, Z.Y.[Zheng-Yi], Xiang, Q.[Qian], Tang, J.T.[Ji-Ting], Wang, Y.[Yuan], Zhao, P.[Peng],
Robust salient object detection for RGB images,
VC(36), No. 9, September 2020, pp. 1823-1835.
WWW Link. 2008
BibRef

Zhou, S., Wang, J., Zhang, J., Wang, L., Huang, D., Du, S., Zheng, N.,
Hierarchical U-Shape Attention Network for Salient Object Detection,
IP(29), 2020, pp. 8417-8428.
IEEE DOI 2008
Object detection, Fuses, Training, Feature extraction, Shape, Memory management, Heating systems, Salient object detection, attention regularization BibRef

Zhou, S., Wang, J., Wang, L., Zhang, J., Wang, F., Huang, D., Zheng, N.,
Hierarchical and Interactive Refinement Network for Edge-Preserving Salient Object Detection,
IP(30), 2021, pp. 1-14.
IEEE DOI 2011
Image edge detection, Object detection, Feature extraction, Inference algorithms, Training, Prediction algorithms, Semantics, Hierarchical and Interactive Refinement Network BibRef

Tang, W.[Wei], Wang, Z.J.[Zhi-Jian], Zhai, J.Y.[Ji-You], Yang, Z.J.[Zhang-Jing],
Salient object detection via two-stage absorbing Markov chain based on background and foreground,
JVCIR(71), 2020, pp. 102727.
Elsevier DOI 2009
Saliency object detection, Markov chain, Background absorbing, Foreground absorbing BibRef

Sun, P., Chen, G., Shang, Y.,
Adaptive Saliency Biased Loss for Object Detection in Aerial Images,
GeoRS(58), No. 10, October 2020, pp. 7154-7165.
IEEE DOI 2009
Detectors, Training, Object detection, Feature extraction, Neural networks, Remote sensing, Benchmark testing, Retinanet BibRef

Wang, T.[Tao], He, X.M.[Xu-Ming], Cai, Y.Z.[Yuan-Zheng], Xiao, G.B.[Guo-Bao],
Learning a Layout Transfer Network for Context Aware Object Detection,
ITS(21), No. 10, October 2020, pp. 4209-4224.
IEEE DOI 2010
Layout, Object detection, Estimation, Context modeling, Cognition, Feature extraction, scene layout transfer BibRef

Zhu, L., Chen, J., Hu, X., Fu, C.W., Xu, X., Qin, J., Heng, P.A.,
Aggregating Attentional Dilated Features for Salient Object Detection,
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Feature extraction, Saliency detection, Object detection, Aggregates, Task analysis, Visualization, Benchmark testing, multiple layer aggregation BibRef

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Object segmentation, Feature extraction, Visualization, Semantics, Image segmentation, Decoding, Aggregates, attention BibRef

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Object detection, Training, Benchmark testing, Observers, Feature extraction, Measurement, Manuals, Saliency, saliency ranking, benchmark. Decoding, Task analysis, Semantics, Observers, Labeling BibRef

Jia, S., Bruce, N.D.B.,
Revisiting Saliency Metrics: Farthest-Neighbor Area Under Curve,
CVPR20(2664-2673)
IEEE DOI 2008
Measurement, Standards, Smoothing methods, Predictive models, Benchmark testing, Training, Robustness BibRef

Wang, A.,
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IEEE DOI 2101
Feature extraction, Saliency detection, Fuses, Visualization, Streaming media, salient object detection BibRef

Wang, L., Chen, R., Zhu, L., Xie, H., Li, X.,
Deep Sub-Region Network for Salient Object Detection,
CirSysVideo(31), No. 2, February 2021, pp. 728-741.
IEEE DOI 2102
Feature extraction, Saliency detection, Object detection, Semantics, Benchmark testing, Visualization, parallel atrous spatial pyramid pooling (ASPP) modules BibRef

Liu, Y.Z.[Yan-Zhu], Wang, Y.N.[Ya-Nan], Kong, A.W.K.[Adams Wai Kin],
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IVC(106), 2021, pp. 104086.
Elsevier DOI 2102
Ordinal classification, Salient object grading, Deep neural networks BibRef

Tu, Z., Ma, Y., Li, C., Tang, J., Luo, B.,
Edge-Guided Non-Local Fully Convolutional Network for Salient Object Detection,
CirSysVideo(31), No. 2, February 2021, pp. 582-593.
IEEE DOI 2102
Image edge detection, Feature extraction, Object detection, Saliency detection, Deep learning, Convolution, Context modeling, fully convolutional neural network BibRef

Hu, X., Fu, C.W., Zhu, L., Wang, T., Heng, P.A.,
SAC-Net: Spatial Attenuation Context for Salient Object Detection,
CirSysVideo(31), No. 3, March 2021, pp. 1079-1090.
IEEE DOI 2103
Attenuation, Feature extraction, Object detection, Aggregates, Semantics, Spatial resolution, Spatial attenuation context, deep learning BibRef

Wu, Y.H.[Yun-He], Jia, T.[Tong], Pang, Y.[Yu], Sun, J.[Jiaduo], Xue, D.[Dingyu],
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Elsevier DOI 2103
Salient object detection, Coarse saliency map, Weighting integration framework, Iterative propagation mechanism BibRef

Shi, C.J.[Cai-Juan], Zhang, W.M.[Wei-Ming], Duan, C.Y.[Chang-Yu], Chen, H.[Houru],
A pooling-based feature pyramid network for salient object detection,
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Elsevier DOI 2103
Salient object detection, U-shaped feature pyramid, Pooling, Convolutional neural network, Deep feature learning BibRef

Liu, Y., Zhang, X.Y., Bian, J.W., Zhang, L., Cheng, M.M.,
SAMNet: Stereoscopically Attentive Multi-Scale Network for Lightweight Salient Object Detection,
IP(30), 2021, pp. 3804-3814.
IEEE DOI 2104
Stereo image processing, Object detection, Task analysis, Fuses, Deep learning, Visualization, Semantics, multi-scale learning BibRef

Ma, G.X.[Guang-Xiao], Li, S.[Shuai], Chen, C.Z.[Chengli-Zhao], Hao, A.[Aimin], Qin, H.[Hong],
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IP(30), 2021, pp. 4238-4252.
IEEE DOI 2104
Semantics, Visualization, Object detection, Computational modeling, Image color analysis, Training, Feature extraction, object-level ranking BibRef

Wang, H.B.[Hai-Bo], Yu, W.Y.[Wen-Yong], You, J.B.[Jiang-Bin], Ma, R.L.[Ruo-Lin], Wang, W.L.[Wei-Lin], Li, B.[Bo],
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Tang, L.[Lv], Li, B.[Bo],
Class: Cross-level Attention and Supervision for Salient Objects Detection,
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Springer DOI 2103
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Gao, S.H.[Shang-Hua], Tan, Y.Q.A.[Yong-Qi-Ang], Cheng, M.M.[Ming-Ming], Lu, C.Z.[Cheng-Ze], Chen, Y.P.[Yun-Peng], Yan, S.C.[Shui-Cheng],
Highly Efficient Salient Object Detection with 100k Parameters,
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Springer DOI 2011
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Li, Y., Chen, X., Quan, L., Zhang, N.,
Loss Rescaling by Uncertainty Inference For Single-Stage Object Detection,
ICIP20(698-702)
IEEE DOI 2011
Uncertainty, Training, Bayes methods, Object detection, Detectors, Task analysis, Image classification, Bayesian neural network, Hard example mining BibRef

Li, B.R.[Bo-Ren], Zhuang, P.Y.[Po-Yu], Gu, J.[Jian], Li, M.Y.[Ming-Yang], Tan, P.[Ping],
Interpretable Foreground Object Search as Knowledge Distillation,
ECCV20(XXVIII:189-204).
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Zhang, J., Yu, X., Li, A., Song, P., Liu, B., Dai, Y.,
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

Wei, J., Wang, S., Wu, Z., Su, C., Huang, Q., Tian, Q.,
Label Decoupling Framework for Salient Object Detection,
CVPR20(13022-13031)
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Bardhan, S.,
Salient Object Detection by Contextual Refinement,
WiCV20(1464-1472)
IEEE DOI 2008
Context modeling, Saliency detection, Customer relationship management, Visualization, Feature extraction BibRef

Zhao, J., Liu, J., Fan, D., Cao, Y., Yang, J., Cheng, M.,
EGNet: Edge Guidance Network for Salient Object Detection,
ICCV19(8778-8787)
IEEE DOI 2004
Code, Object Detection.
WWW Link. convolutional neural nets, edge detection, feature extraction, image fusion, object detection, edge guidance network, Fuses BibRef

Wu, Z., Su, L., Huang, Q.,
Stacked Cross Refinement Network for Edge-Aware Salient Object Detection,
ICCV19(7263-7272)
IEEE DOI 2004
Code, Object Detection.
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Su, J., Li, J., Zhang, Y., Xia, C., Tian, Y.,
Selectivity or Invariance: Boundary-Aware Salient Object Detection,
ICCV19(3798-3807)
IEEE DOI 2004
object detection, complex interior perception stream, transition compensation stream, feature invariance, Saliency detection BibRef

Zeng, L.Y.[Ling-Yun], Song, Y.[You], Wang, W.[Wenhai],
Guided Refine-head for Object Detection,
MMMod20(I:203-214).
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Zhang, J.L.[Jun-Lin], Wang, X.[Xu],
Light Field Salient Object Detection via Hybrid Priors,
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Cascaded Partial Decoder for Fast and Accurate Salient Object Detection,
CVPR19(3902-3911).
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Liu, J.J.[Jiang-Jiang], Hou, Q.[Qibin], Cheng, M.M.[Ming-Ming], Feng, J.[Jiashi], Jiang, J.M.[Jian-Min],
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CVPR19(3912-3921).
IEEE DOI 2002
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Wu, R.M.[Run-Min], Feng, M.Y.[Meng-Yang], Guan, W.L.[Wen-Long], Wang, D.[Dong], Lu, H.C.[Hu-Chuan], Ding, E.[Errui],
A Mutual Learning Method for Salient Object Detection With Intertwined Multi-Supervision,
CVPR19(8142-8151).
IEEE DOI 2002
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Qin, X.B.[Xue-Bin], Zhang, Z.C.[Zi-Chen], Huang, C.Y.[Chen-Yang], Gao, C.[Chao], Dehghan, M.[Masood], Jagersand, M.[Martin],
BASNet: Boundary-Aware Salient Object Detection,
CVPR19(7471-7481).
IEEE DOI 2002
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Wang, W.G.[Wen-Guan], Shen, J.B.[Jian-Bing], Cheng, M.M.[Ming-Ming], Shao, L.[Ling],
An Iterative and Cooperative Top-Down and Bottom-Up Inference Network for Salient Object Detection,
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Xu, Y.Y.[Ying-Yue], Hong, X.P.[Xiao-Peng], Zhao, G.Y.[Guo-Ying],
Salient Object Detection with CNNs and Multi-scale CRFs,
SCIA19(233-245).
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Pan, C., Li, X., Yan, W.Q.,
A Learning-Based Positive Feedback Approach in Salient Object Detection,
IVCNZ18(1-6)
IEEE DOI 1902
Feedback loop, Saliency detection, Visual systems, Computational modeling, Training, Neural networks, Visualization BibRef

Hu, H., Gu, J., Zhang, Z., Dai, J., Wei, Y.,
Relation Networks for Object Detection,
CVPR18(3588-3597)
IEEE DOI 1812
Object detection, Task analysis, Feature extraction, Geometry, Detectors, Manganese, Computational modeling BibRef

Kosugi, S., Yamasaki, T., Aizawa, K.,
Object-Aware Instance Labeling for Weakly Supervised Object Detection,
ICCV19(6063-6071)
IEEE DOI 2004
image annotation, image classification, iterative methods, learning (artificial intelligence), object detection, Focusing BibRef

Inoue, N., Furuta, R., Yamasaki, T., Aizawa, K.,
Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation,
CVPR18(5001-5009)
IEEE DOI 1812
Object detection, Task analysis, Detectors, Dogs, Search engines, Feature extraction, Noise measurement BibRef

Wang, J., Xing, Y., Zeng, G.,
Global Context Encoding for Salient Objects Detection,
ICPR18(2337-2342)
IEEE DOI 1812
Encoding, Object detection, Task analysis, Semantics, Feature extraction, Image segmentation, Computer vision BibRef

Zhang, L., Dai, J., Lu, H., He, Y., Wang, G.,
A Bi-Directional Message Passing Model for Salient Object Detection,
CVPR18(1741-1750)
IEEE DOI 1812
Feature extraction, Bidirectional control, Message passing, Object detection, Logic gates, Semantics, Task analysis BibRef

Gao, M., Yu, R., Li, A., Morariu, V.I., Davis, L.S.,
Dynamic Zoom-in Network for Fast Object Detection in Large Images,
CVPR18(6926-6935)
IEEE DOI 1812
Detectors, Image resolution, Proposals, History, Computational efficiency, Convolution, Object detection BibRef

Mishkin, D.[Dmytro], Radenovic, F.[Filip], Matas, J.G.[Jiri G.],
Repeatability Is Not Enough: Learning Affine Regions via Discriminability,
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Kim, S.W.[Seung-Wook], Kook, H.K.[Hyong-Keun], Sun, J.Y.[Jee-Young], Kang, M.C.[Mun-Cheon], Ko, S.J.[Sung-Jea],
Parallel Feature Pyramid Network for Object Detection,
ECCV18(VI: 239-256).
Springer DOI 1810
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Li, Z.[Zeming], Peng, C.[Chao], Yu, G.[Gang], Zhang, X.Y.[Xiang-Yu], Deng, Y.D.[Yang-Dong], Sun, J.[Jian],
DetNet: Design Backbone for Object Detection,
ECCV18(IX: 339-354).
Springer DOI 1810
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Fan, D.P.[Deng-Ping], Cheng, M.M.[Ming-Ming], Liu, J.J.[Jiang-Jiang], Gao, S.H.[Shang-Hua], Hou, Q.[Qibin], Borji, A.[Ali],
Salient Objects in Clutter: Bringing Salient Object Detection to the Foreground,
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Springer DOI 1810
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Wang, T., Borji, A., Zhang, L., Zhang, P., Lu, H.,
A Stagewise Refinement Model for Detecting Salient Objects in Images,
ICCV17(4039-4048)
IEEE DOI 1802
convolution, feature extraction, feedforward, image resolution, image segmentation, neural nets, Visualization BibRef

Li, X.[Xin], Yang, F.[Fan], Cheng, H.[Hong], Liu, W.[Wei], Shen, D.G.[Ding-Gang],
Contour Knowledge Transfer for Salient Object Detection,
ECCV18(XV: 370-385).
Springer DOI 1810
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Zhang, S.Q.[Shi-Quan], Zhao, X.[Xu], Fang, L.J.[Liang-Ji], Fei, H.P.[Hai-Ping], Song, H.T.[Hai-Tao],
LED: Localization-Quality Estimation Embedded Detector,
ICIP18(584-588)
IEEE DOI 1809
Light emitting diodes, Estimation, Detectors, Automobiles, Feature extraction, Training, Object detection, One-stage Detector BibRef

Huang, K., Zhu, C., Li, G.,
Robust Salient Object Detection via Fusing Foreground and Background Priors,
ICIP18(2341-2345)
IEEE DOI 1809
Estimation, Object detection, Principal component analysis, Robustness, Task analysis, Image segmentation, geodesic distance BibRef

Yu, R.[Ruichi], Chen, X.[Xi], Morariu, V.[Vlad], Davis, L.S.[Larry S.],
The Role of Context Selection in Object Detection,
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Enhancing Saliency of an Object Using Genetic Algorithm,
CRV17(337-344)
IEEE DOI 1804
feature extraction, genetic algorithms, image segmentation, object detection, visual perception, feature dissimilarity, genetic algorithm BibRef

Kuan, K., Manek, G., Lin, J., Fang, Y., Chandrasekhar, V.,
Region average pooling for context-aware object detection,
ICIP17(1347-1351)
IEEE DOI 1803
Computer vision, Feature extraction, Object detection, Proposals, Task analysis, Testing, Training, CNN, Context, Faster R-CNN, Pooling BibRef

Zhang, D., Han, J., Zhang, Y.,
Supervision by Fusion: Towards Unsupervised Learning of Deep Salient Object Detector,
ICCV17(4068-4076)
IEEE DOI 1802
convolution, image fusion, neural nets, object detection, unsupervised learning, DNNs, deep convolutional models, Unsupervised learning BibRef

Fan, D.P., Cheng, M.M., Liu, Y., Li, T., Borji, A.,
Structure-Measure: A New Way to Evaluate Foreground Maps,
ICCV17(4558-4567)
IEEE DOI 1802
image segmentation, object detection, SM, Structure-measure, behavioral vision studies, evaluate foreground, Prediction algorithms BibRef

Rekik, F.[Farah], Ayedi, W.[Walid], Jallouli, M.[Mohamed],
Performance Evaluation of Multiscale Covariance Descriptor in Underwater Object Detection,
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Luo, Z., Mishra, A., Achkar, A., Eichel, J., Li, S., Jodoin, P.M.,
Non-local Deep Features for Salient Object Detection,
CVPR17(6593-6601)
IEEE DOI 1711
Computational modeling, Convolution, Feature extraction, Image resolution, Image segmentation, Machine learning, Predictive, models BibRef

Zhou, L., Yang, S., Yang, Y., Yang, Z.,
Geodesic distance and compactness prior based salient region detection,
ICVNZ16(1-5)
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Diffusion processes BibRef

López-Sastre, R.J.[Roberto J.],
Unsupervised Robust Feature-Based Partition Ensembling to Discover Categories,
Robust16(1187-1195)
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Different features to aggregate different partitions to get objects. BibRef

Cholakkal, H.[Hisham], Johnson, J.[Jubin], Rajan, D.[Deepu],
Backtracking ScSPM Image Classifier for Weakly Supervised Top-Down Saliency,
CVPR16(5278-5287)
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Lee, G.Y.[Ga-Young], Tai, Y.W.[Yu-Wing], Kim, J.[Junmo],
Deep Saliency with Encoded Low Level Distance Map and High Level Features,
CVPR16(660-668)
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Salient regions BibRef

Kim, J.[Jongpil], Pavlovic, V.[Vladimir],
A shape preserving approach for salient object detection using convolutional neural networks,
ICPR16(609-614)
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A Shape-Based Approach for Salient Object Detection Using Deep Learning,
ECCV16(IV: 455-470).
Springer DOI 1611
Computational modeling, Image segmentation, Neural networks, Object detection, Proposals, Shape, Training BibRef

Filali, I.[Idir], Allili, M.S.[Mohand Said], Benblidia, N.[Nadjia],
Multi-graph Based Salient Object Detection,
ICIAR16(318-324).
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Zou, W., Komodakis, N.,
HARF: Hierarchy-Associated Rich Features for Salient Object Detection,
ICCV15(406-414)
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Biological system modeling BibRef

Xiang, D.[Dan], Zhong, B.[Baojiang], Ma, K.K.[Kai-Kuang],
A location-aware scale-space method for salient object detection,
ICIP15(4195-4199)
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Saliency detection BibRef

Hati, A.[Avik], Chaudhuri, S.[Subhasis], Velmurugan, R.[Rajbabu],
Salient object carving,
ICIP15(1767-1771)
IEEE DOI 1512
Saliency; seam carving; texture removal BibRef

Yildirim, G.[Gökhan], Süsstrunk, S.[Sabine],
FASA: Fast, Accurate, and Size-Aware Salient Object Detection,
ACCV14(III: 514-528).
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Zhao, L.[Long], Liang, S.[Shuang], Wei, Y.C.[Yi-Chen], Jia, J.Y.[Jin-Yuan],
Size and Location Matter: A New Baseline for Salient Object Detection,
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Zhou, Q.[Quan], Cai, S.[Shu], Zhu, S.J.[Shao-Jun], Zheng, B.[Baoyu],
Salient Object Detection Using Window Mask Transferring with Multi-layer Background Contrast,
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Lu, S.J.[Shi-Jian], Kim, B.U.[Byung-Uck], Lomenie, N.[Nicolas], Lim, J.H.[Joo-Hwee], Cai, J.F.[Jian-Fei],
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ICIP14(1145-1149)
IEEE DOI 1502
Bismuth BibRef

Gao, H.Y.[Hong-Yun], Lam, K.M.[Kin-Man],
Salient object detection using octonion with Bayesian inference,
ICIP14(3292-3296)
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Holzbach, A.[Andreas], Cheng, G.[Gordon],
A scalable and efficient method for salient region detection using sampled template collation,
ICIP14(1110-1114)
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Benchmark testing BibRef

Li, Y.[Yin], Hou, X.D.[Xiao-Di], Koch, C.[Christof], Rehg, J.M.[James M.], Yuille, A.L.[Alan L.],
The Secrets of Salient Object Segmentation,
CVPR14(280-287)
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Saliency; dataset analysis; eye fixation; salient object segmentation BibRef

He, S.F.[Sheng-Feng], Lau, R.W.H.[Rynson W. H.],
Exemplar-Driven Top-Down Saliency Detection via Deep Association,
CVPR16(5723-5732)
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Only closer (foreground or salient) objects are well lit by the flash. BibRef

Cao, H.[Hai], Li, S.Z.[Shao-Zi], Su, S.Z.[Song-Zhi], Cheng, Y.[Yun], Ji, R.R.[Rong-Rong],
Saliency detection by adaptive clustering,
VCIP13(1-6)
IEEE DOI 1402
feature extraction BibRef

Cheng, M.M.[Ming-Ming], Warrell, J.[Jonathan], Lin, W.Y.[Wen-Yan], Zheng, S.[Shuai], Vineet, V.[Vibhav], Crook, N.[Nigel],
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ICCV13(1529-1536)
IEEE DOI 1403
image abstraction BibRef

Jia, Y.Q.[Yang-Qing], Han, M.[Mei],
Category-Independent Object-Level Saliency Detection,
ICCV13(1761-1768)
IEEE DOI 1403
objectness; saliency detection BibRef

Li, X.[Xi], Li, Y.[Yao], Shen, C.H.[Chun-Hua], Dick, A.[Anthony], van den Hengel, A.J.[Anton J.],
Contextual Hypergraph Modeling for Salient Object Detection,
ICCV13(3328-3335)
IEEE DOI 1403
Saliency detection; Salient Object Detection BibRef

Jiang, P.[Peng], Ling, H.B.[Hai-Bin], Yu, J.Y.[Jing-Yi], Peng, J.L.[Jing-Liang],
Salient Region Detection by UFO: Uniqueness, Focusness and Objectness,
ICCV13(1976-1983)
IEEE DOI 1403
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Zhu, L.[Lei], Klein, D.A.[Dominik A.], Frintrop, S.[Simone], Cao, Z.G.[Zhi-Guo], Cremers, A.B.[Armin B.],
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ICIP13(176-180)
IEEE DOI 1402
Benchmark testing BibRef

Zhang, Z.Z.[Zhen-Zhen], Cao, J.J.[Jun-Jie], Zhong, G.Y.[Guang-Yu], Liu, W.Y.[Wang-Yi], Su, Z.[Zhixun],
Object level image saliency by hierarchical segmentation,
ICIP13(1772-1776)
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Object level image saliency BibRef

Liang, J.[Jie], Zhou, J.[Jun], Bai, X.[Xiao], Qian, Y.T.[Yun-Tao],
Salient object detection in hyperspectral imagery,
ICIP13(2393-2397)
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Saliency detection;hyperspectral imaging;object detection BibRef

Shuai, J.[Jiamei], Qing, L.Y.[Lai-Yun], Miao, J.[Jun], Ma, Z.G.[Zhi-Guo], Chen, X.L.[Xi-Lin],
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ICIP13(2470-2474)
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Fu, K.[Keren], Gong, C.[Chen], Gu, I.Y.H.[Irene Y.H.], Yang, J.[Jie],
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ICIP13(3426-3430)
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Salient object detection;compactness;superpixel BibRef

Schauerte, B., Stiefelhagen, R.,
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ICIP13(74-78)
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A Global-Local Approach to Saliency Detection,
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SCIA13(85-94).
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Salient Object Detection: A Discriminative Regional Feature Integration Approach,
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Jiang, H.Z.[Huai-Zu], Wang, J.D.[Jing-Dong], Yuan, Z.J.[Ze-Jian], Wu, Y.[Yang], Zheng, N.N.[Nan-Ning], Li, S.P.[Shi-Peng],
Salient Object Detection: A Discriminative Regional Feature Integration Approach C,
CVPR13(2083-2090)
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ICIP12(1073-1076).
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Saliency detection based on integration of boundary and soft-segmentation,
ICIP12(1085-1088).
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Tang, H.[Hao],
Object-aware saliency detection for consumer images,
ICIP12(1097-1100).
IEEE DOI 1302
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Wang, P.[Peng], Wang, J.D.[Jing-Dong], Zeng, G.[Gang], Feng, J.[Jie], Zha, H.B.[Hong-Bin], Li, S.P.[Shi-Peng],
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CVPR12(3194-3201).
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CVPR12(853-860).
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Real-time visual saliency by Division of Gaussians,
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High resolution biologically inspired salient region detection,
ICIP11(649-652).
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Xie, Y.L.[Yu-Lin], Lu, H.C.[Hu-Chuan],
Visual saliency detection based on Bayesian model,
ICIP11(645-648).
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Jiang, H.Z.[Huai-Zu], Wang, J.D.[Jing-Dong], Yuan, Z.J.[Ze-Jian], Liu, T.[Tie], Zheng, N.N.[Nan-Ning],
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Pei, C.[Chaoke], Gao, L.[Li], Wang, D.H.[Dong-Hui], Hong, Y.[Ying],
A PFT Visual Attention Detection Model Using Bayesian Framework,
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Duan, L.J.[Li-Juan], Wu, C.P.[Chun-Peng], Miao, J.[Jun], Qing, L.Y.[Lai-Yun], Fu, Y.[Yu],
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CVPR11(473-480).
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Vikram, T.N.[Tadmeri Narayan], Tscherepanow, M.[Marko], Wrede, B.[Britta],
A random center surround bottom up visual attention model useful for salient region detection,
WACV11(166-173).
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Dong, M.[Ming], Chen, Y.H.[Yan-Hua],
Salient region detection and feature extraction in 3D visual data,
ICIP08(185-188).
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Chapter on 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture continues in
Color for Salient Regions .

Last update:Apr 19, 2021 at 11:17:57