-
2
-
-
84870220894
-
-
State-of-the-art in visual attention modeling, IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 35 (1) (2013) 185–207
-
[2] A. Borji, L. Itti, State-of-the-art in visual attention modeling, IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 35 (1) (2013) 185–207.
-
-
-
Borji, A.1
Itti, L.2
-
3
-
-
35148814949
-
Saliency detection: a spectral residual approach,
-
[3] X. Hou, L. Zhang, Saliency detection: a spectral residual approach, In: CVPR, 2007.
-
(2007)
CVPR
-
-
Hou, X.1
Zhang, L.2
-
4
-
-
79952521969
-
Segmenting Salient Objects from Images and Videos,
-
[4] E. Rahtu, J. Kannala, M. Salo, J. Heikkila, Segmenting Salient Objects from Images and Videos, In: ECCV, 2010.
-
(2010)
ECCV
-
-
Rahtu, E.1
Kannala, J.2
Salo, M.3
Heikkila, J.4
-
5
-
-
84863052350
-
Automatic Salient Object Extraction with Contextual Cue,
-
[5] L. Wang, J. Xue, N. Zheng, G. Hua, Automatic Salient Object Extraction with Contextual Cue, In: ICCV, 2011.
-
(2011)
ICCV
-
-
Wang, L.1
Xue, J.2
Zheng, N.3
Hua, G.4
-
7
-
-
77953210642
-
-
A framework for visual saliency detection with applications to image thumbnailing, In: ICCV, 2009.
-
[7] L. Marchesotti, et al., A framework for visual saliency detection with applications to image thumbnailing, In: ICCV, 2009.
-
-
-
Marchesotti, L.1
-
8
-
-
80052908132
-
Importance filtering for image retargeting,
-
[8] Y. Ding, X. Jing, J. Yu, Importance filtering for image retargeting, In: CVPR, 2011.
-
(2011)
CVPR
-
-
Ding, Y.1
Jing, X.2
Yu, J.3
-
9
-
-
77956008283
-
-
Context-aware saliency detection, In: CVPR, 2010.
-
[9] S. Goferman, et al., Context-aware saliency detection, In: CVPR, 2010.
-
-
-
Goferman, S.1
-
10
-
-
77749271171
-
Sketch2photo: internet image montage
-
[10] Chen, T., Cheng, M., et al. Sketch2photo: internet image montage. ACM Trans. Graph 28:5 (2006), 1–10.
-
(2006)
ACM Trans. Graph
, vol.28
, Issue.5
, pp. 1-10
-
-
Chen, T.1
Cheng, M.2
-
11
-
-
34547210110
-
Visual attention detection in video sequences using spatiotemporal cues
-
[11] Zhai, Y., Shah, M., Visual attention detection in video sequences using spatiotemporal cues. ACM Multimed., 2006, 815–824.
-
(2006)
ACM Multimed.
, pp. 815-824
-
-
Zhai, Y.1
Shah, M.2
-
12
-
-
78049391450
-
Frequency-tuned salient region detection,
-
[12] R. Achanta, S. Hemami, F. Estrada, S. Süsstrunk, Frequency-tuned salient region detection, In: CVPR, 2009.
-
(2009)
CVPR
-
-
Achanta, R.1
Hemami, S.2
Estrada, F.3
Süsstrunk, S.4
-
13
-
-
80052948224
-
Global contrast based salient region detection,
-
[13] M. Cheng, G. Zhang, N. Mitra, X. Huang, S. Hu, Global contrast based salient region detection, In: CVPR, 2011.
-
(2011)
CVPR
-
-
Cheng, M.1
Zhang, G.2
Mitra, N.3
Huang, X.4
Hu, S.5
-
14
-
-
84898491541
-
-
Automatic salient object segmentation based on context and shape prior, In: BMVC, 2011.
-
[14] H. Jiang, J. Wang, et al., Automatic salient object segmentation based on context and shape prior, In: BMVC, 2011.
-
-
-
Jiang, H.1
Wang, J.2
-
15
-
-
84866667038
-
-
Saliency filters: contrast based filtering for salient region detection, In: CVPR, 2012.
-
[15] F. Perazzi, P. Krahenbul, et al., Saliency filters: contrast based filtering for salient region detection, In: CVPR, 2012.
-
-
-
Perazzi, F.1
Krahenbul, P.2
-
16
-
-
84933044434
-
-
Pisa: pixelwise image saliency by aggregating complementary appearance contrast measures with edge-preserving coherence, IEEE Trans. Image Process. (IP) 24 (10) (2015) 3019–3033
-
[16] K. Wang, L. Lin, J. Lu, C. Li, K. Shi, Pisa: pixelwise image saliency by aggregating complementary appearance contrast measures with edge-preserving coherence, IEEE Trans. Image Process. (IP) 24 (10) (2015) 3019–3033.
-
-
-
Wang, K.1
Lin, L.2
Lu, J.3
Li, C.4
Shi, K.5
-
17
-
-
84887392014
-
-
Salient object detection: a discriminative regional feature integration approach, In: CVPR, 2013.
-
[17] H. Jiang, et al., Salient object detection: a discriminative regional feature integration approach, In: CVPR, 2013.
-
-
-
Jiang, H.1
-
18
-
-
78650512633
-
Learning to detect a salient object
-
[18] Liu, T., Yuan, Z., Sun, J., Wang, J., Zheng, N., Learning to detect a salient object. TPAMI 33:2 (2011), 353–367.
-
(2011)
TPAMI
, vol.33
, Issue.2
, pp. 353-367
-
-
Liu, T.1
Yuan, Z.2
Sun, J.3
Wang, J.4
Zheng, N.5
-
19
-
-
84887368846
-
Saliency aggregation: a data-driven approach,
-
[19] L. Mai, Y. Niu, F. Liu, Saliency aggregation: a data-driven approach, In: CVPR, 2013.
-
(2013)
CVPR
-
-
Mai, L.1
Niu, Y.2
Liu, F.3
-
20
-
-
84863014296
-
Salient object detection using concavity context,
-
[20] Y. Lu, W. Zhang, H. Lu, X. Xue, Salient object detection using concavity context, In: IEEE International Conference on Computer Vision (ICCV), 2011.
-
(2011)
IEEE International Conference on Computer Vision (ICCV)
-
-
Lu, Y.1
Zhang, W.2
Lu, H.3
Xue, X.4
-
21
-
-
84887322898
-
-
Hierarchical saliency detection, In: CVPR, 2013.
-
[21] Q. Yan, et al., Hierarchical saliency detection, In: CVPR, 2013.
-
-
-
Yan, Q.1
-
22
-
-
84898797836
-
-
Efficient salient region detection with soft image abstraction, In: ICCV, 2013.
-
[22] M. Cheng, J. Warrell, et al., Efficient salient region detection with soft image abstraction, In: ICCV, 2013.
-
-
-
Cheng, M.1
Warrell, J.2
-
24
-
-
78649256287
-
Random walks on graphs for salient object detection in images
-
[24] Gopalakrishnan, V., et al. Random walks on graphs for salient object detection in images. TIP 19:12 (2010), 3232–3242.
-
(2010)
TIP
, vol.19
, Issue.12
, pp. 3232-3242
-
-
Gopalakrishnan, V.1
-
25
-
-
84887344857
-
Geodesic saliency using background priors,
-
[25] Y. Wei, F. Wen, W. Zhu, J. Sun, Geodesic saliency using background priors, In: ECCV, 2012.
-
(2012)
ECCV
-
-
Wei, Y.1
Wen, F.2
Zhu, W.3
Sun, J.4
-
26
-
-
84887357058
-
-
Saliency detection via graph-based manifold ranking, In: CVPR, 2013.
-
[26] C. Yang, L. Zhang, et al., Saliency detection via graph-based manifold ranking, In: CVPR, 2013.
-
-
-
Yang, C.1
Zhang, L.2
-
27
-
-
84897788972
-
Geodesic saliency propagation for image salient region detection,
-
[27] K. Fu, C. Gong, I. Gu, J. Yang, Geodesic saliency propagation for image salient region detection, In: ICIP, 2013.
-
(2013)
ICIP
-
-
Fu, K.1
Gong, C.2
Gu, I.3
Yang, J.4
-
28
-
-
85119024889
-
-
Learning optimal seeds for diffusion-based salient object detection, In: CVPR, 2014.
-
[28] S. Lu, V. Mahadevan, et al., Learning optimal seeds for diffusion-based salient object detection, In: CVPR, 2014.
-
-
-
Lu, S.1
Mahadevan, V.2
-
29
-
-
85020531812
-
-
Learning with local and global consistency, In: NIPS, 2003.
-
[29] D. Zhou, et al., Learning with local and global consistency, In: NIPS, 2003.
-
-
-
Zhou, D.1
-
30
-
-
84899013566
-
-
Ranking on data manifolds, In: NIPS, 2004.
-
[30] D. Zhou, et al., Ranking on data manifolds, In: NIPS, 2004.
-
-
-
Zhou, D.1
-
31
-
-
67650272548
-
Introduction to semi-supervised learning
-
[31] Zhu, X., Goldberg, A., Introduction to semi-supervised learning. Synthesis lectures on artificial intelligence and machine learning 3:1 (2009), 1–130.
-
(2009)
Synthesis lectures on artificial intelligence and machine learning
, vol.3
, Issue.1
, pp. 1-130
-
-
Zhu, X.1
Goldberg, A.2
-
32
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
[32] Roweis, S., Saul, L., Nonlinear dimensionality reduction by locally linear embedding. Science 290:5500 (2000), 2323–2326.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2323-2326
-
-
Roweis, S.1
Saul, L.2
-
33
-
-
67650998686
-
Linear neighborhood propagation and its applications
-
[33] Wang, J., Wang, F., Zhang, C., et al. Linear neighborhood propagation and its applications. IEEE Trans. Pattern Anal. Mach. Intell. 31:9 (2009), 1600–1615.
-
(2009)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.31
, Issue.9
, pp. 1600-1615
-
-
Wang, J.1
Wang, F.2
Zhang, C.3
-
34
-
-
84921030558
-
Saliency detection via background and foreground seed selection
-
[34] Wang, J., Lu, H., Li, X., Tong, N., Lei, W., Saliency detection via background and foreground seed selection. Neurocomputing 152 (2015), 359–368.
-
(2015)
Neurocomputing
, vol.152
, pp. 359-368
-
-
Wang, J.1
Lu, H.2
Li, X.3
Tong, N.4
Lei, W.5
-
35
-
-
84937874239
-
Deep joint task learning for generic object extraction,
-
[35] X. Wang, L. Zhang, L. Lin, Z. Liang, W. Zuo, Deep joint task learning for generic object extraction, In: NIPS, 2014.
-
(2014)
NIPS
-
-
Wang, X.1
Zhang, L.2
Lin, L.3
Liang, Z.4
Zuo, W.5
-
36
-
-
84866672748
-
A unified approach to salient object detection via low rank matrix recovery,
-
[36] X. Shen, Y. Wu, A unified approach to salient object detection via low rank matrix recovery, In: CVPR, 2012.
-
(2012)
CVPR
-
-
Shen, X.1
Wu, Y.2
-
37
-
-
84856273418
-
Visual saliency detection based on Bayesian model,
-
[37] Y. Xie, H. Lu, Visual saliency detection based on Bayesian model, In: ICIP, 2011.
-
(2011)
ICIP
-
-
Xie, Y.1
Lu, H.2
-
38
-
-
85020525351
-
-
What makes a patch distinct, In: CVPR, 2013.
-
[38] R. Margolin, et al., What makes a patch distinct, In: CVPR, 2013.
-
-
-
Margolin, R.1
-
39
-
-
84898822478
-
Saliency detection via dense and sparse reconstruction,
-
[39] X. Li, H. Lu, L. Zhang, X. Ruan, M. Yang, Saliency detection via dense and sparse reconstruction, In: ICCV, 2013.
-
(2013)
ICCV
-
-
Li, X.1
Lu, H.2
Zhang, L.3
Ruan, X.4
Yang, M.5
-
40
-
-
84866657764
-
-
Slic superpixels compared to state-of-the-art superpixel methods, IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 34 (11) (2012) 2274–2282
-
[40] R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, S. Susstrunk, Slic superpixels compared to state-of-the-art superpixel methods, IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 34 (11) (2012) 2274–2282.
-
-
-
Achanta, R.1
Shaji, A.2
Smith, K.3
Lucchi, A.4
Fua, P.5
Susstrunk, S.6
-
41
-
-
85020533777
-
-
A kernel method for the two-sample-problem, In: NIPS, 2006.
-
[41] A. Gretton, K. Borgwardt, M. Rasch, et al., A kernel method for the two-sample-problem, In: NIPS, 2006.
-
-
-
Gretton, A.1
Borgwardt, K.2
Rasch, M.3
-
42
-
-
33644783522
-
Self-tuning spectral clustering,
-
[42] L. Zelnik-Manor, P. Perona, Self-tuning spectral clustering, In: NIPS, 2004.
-
(2004)
NIPS
-
-
Zelnik-Manor, L.1
Perona, P.2
-
43
-
-
84899028598
-
Manifold-based similarity adaptation for label propagation,
-
[43] M. Karasuyama, H. Mamitsuka, Manifold-based similarity adaptation for label propagation, In: NIPS, 2013.
-
(2013)
NIPS
-
-
Karasuyama, M.1
Mamitsuka, H.2
-
44
-
-
34548583274
-
A tutorial on spectral clustering
-
[44] von Luxburg, U., A tutorial on spectral clustering. Stat. Comput. 17:4 (2007), 395–416.
-
(2007)
Stat. Comput.
, vol.17
, Issue.4
, pp. 395-416
-
-
von Luxburg, U.1
-
45
-
-
85119025159
-
-
Salient region detection via high-dimensional color transform, In: CVPR, 2014.
-
[45] J. Kim, D. Han, Y. Tai, et al., Salient region detection via high-dimensional color transform, In: CVPR, 2014.
-
-
-
Kim, J.1
Han, D.2
Tai, Y.3
-
46
-
-
37549020109
-
A closed-form solution to natural image matting
-
[46] Levin, A., Lischinski, D., Weiss, Y., A closed-form solution to natural image matting. IEEE Trans. Pattern Anal. Mach. Intell. 30:2 (2008), 228–242.
-
(2008)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.30
, Issue.2
, pp. 228-242
-
-
Levin, A.1
Lischinski, D.2
Weiss, Y.3
-
47
-
-
84882376954
-
Guided image filtering
-
[47] He, K., Sun, J., Tang, X., Guided image filtering. IEEE Trans. Pattern Anal. Mach. Intell. 35:6 (2013), 1397–1409.
-
(2013)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.35
, Issue.6
, pp. 1397-1409
-
-
He, K.1
Sun, J.2
Tang, X.3
-
48
-
-
0032204063
-
A model of saliency-based visual attention for rapid scene analysis
-
[48] Itti, L., Koch, C., Niebur, E., A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) 20:11 (1998), 1254–1259.
-
(1998)
IEEE Trans. Pattern Anal. Mach. Intell. (PAMI)
, vol.20
, Issue.11
, pp. 1254-1259
-
-
Itti, L.1
Koch, C.2
Niebur, E.3
-
49
-
-
0018306059
-
A threshold selection method from gray-level histograms
-
[49] Otsu, N., A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9:1 (1979), 62–66.
-
(1979)
IEEE Trans. Syst. Man Cybern.
, vol.9
, Issue.1
, pp. 62-66
-
-
Otsu, N.1
-
50
-
-
84877867280
-
Graph-regularized saliency detection with convex-hull-based center prior
-
[50] Yang, C., Zhang, L., Lu, H., Graph-regularized saliency detection with convex-hull-based center prior. Signal Process. Lett. 20:7 (2013), 647–648.
-
(2013)
Signal Process. Lett.
, vol.20
, Issue.7
, pp. 647-648
-
-
Yang, C.1
Zhang, L.2
Lu, H.3
-
52
-
-
84898025441
-
Saliency tree: a novel saliency detection framework
-
[52] Liu, Z., Zou, W., Meur, O., Saliency tree: a novel saliency detection framework. IEEE Trans. Image Process. 23:5 (2014), 1937–1952.
-
(2014)
IEEE Trans. Image Process.
, vol.23
, Issue.5
, pp. 1937-1952
-
-
Liu, Z.1
Zou, W.2
Meur, O.3
-
54
-
-
34948898079
-
-
Image segmentation by probabilistic bottom-up aggregation and cue integration, In: CVPR, 2007.
-
[54] S. Alpert, M. Galun, et al., Image segmentation by probabilistic bottom-up aggregation and cue integration, In: CVPR, 2007.
-
-
-
Alpert, S.1
Galun, M.2
|