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The use of RGB-D information for salient object detection has been extensively explored in recent years.
E. L. Kaufman, M. W. Lord, T. W. Reese, and J. Volkmann, “The discrimination of visual number,”
1949
Earlier work this paper cites.
D. Martin, C. Fowlkes, D. Tal, and J. Malik, “A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics,” in
2001
Earlier work this paper cites.
R. Ng, M. Levoy, M. Brédif, G. Duval, M. Horowitz, P. Hanrahan
2005
Earlier work this paper cites.
B. W. Tatler, R. J. Baddeley, and I. D. Gilchrist, “Visual correlates of fixation selection: Effects of scale and time,”
2005
Earlier work this paper cites.
S. Alpert, M. Galun, R. Basri, and A. Brandt, “Image segmentation by probabilistic bottom-up aggregation and cue integration,” in
2007
Earlier work this paper cites.
T. Liu, J. Sun, N. Zheng, X. Tang, and H.-Y. Shum, “Learning to detect a salient object,” in
2007
Earlier work this paper cites.
R. Achanta, S. Hemami, F. Estrada, and S. Susstrunk, “Frequency-tuned salient region detection,” in
2009
Earlier work this paper cites.
D. Sun, S. Roth, and M. J. Black, “Secrets of optical flow estimation and their principles,” in
2010
Earlier work this paper cites.
D. Tsai, M. Flagg, and J. Rehg, “Motion coherent tracking with multi-label mrf optimization, algorithms,” in
2010
Earlier work this paper cites.
C. Liu, J. Yuen, and A. Torralba, “Sift flow: Dense correspondence across scenes and its applications,”
2011
Earlier work this paper cites.
P. Sauer, T. F. Cootes, and C. J. Taylor, “Accurate regression procedures for active appearance models.” in
2011
Earlier work this paper cites.
C.-C. Chang and C.-J. Lin, “LIBSVM: a library for support vector machines,”
2011
Earlier work this paper cites.
Z. Zhang, “Microsoft kinect sensor and its effect,”
2012
Earlier work this paper cites.
Y. Niu, Y. Geng, X. Li, and F. Liu, “Leveraging stereopsis for saliency analysis,” in
2012
Earlier work this paper cites.
F. Perazzi, P. Krähenbühl, Y. Pritch, and A. Hornung, “Saliency filters: Contrast based filtering for salient region detection,” in
2012
Earlier work this paper cites.
A. Ciptadi, T. Hermans, and J. M. Rehg, “An in depth view of saliency,” in
2013
Earlier work this paper cites.
K. Desingh, K. M. Krishna, D. Rajan, and C. Jawahar, “Depth really matters: Improving visual salient region detection with depth.” in
2013
Earlier work this paper cites.
Q. Yan, L. Xu, J. Shi, and J. Jia, “Hierarchical saliency detection,” in
2013
Earlier work this paper cites.
A. Jahanian, J. Liu, Q. Lin, D. Tretter, E. O’Brien-Strain, S. C. Lee, N. Lyons, and J. Allebach, “Recommendation system for automatic design of magazine covers,” in
2013
Earlier work this paper cites.
R. Ju, L. Ge, W. Geng, T. Ren, and G. Wu, “Depth saliency based on anisotropic center-surround difference,” in
2014
Earlier work this paper cites.
Y. Cheng, H. Fu, X. Wei, J. Xiao, and X. Cao, “Depth enhanced saliency detection method,” in
2014
Earlier work this paper cites.
H. Peng, B. Li, W. Xiong, W. Hu, and R. Ji, “Rgbd salient object detection: a benchmark and algorithms,” in
2014
Earlier work this paper cites.
R. Margolin, L. Zelnik-Manor, and A. Tal, “How to evaluate foreground maps?” in
2014
Earlier work this paper cites.
N. Li, J. Ye, Y. Ji, H. Ling, and J. Yu, “Saliency detection on light field,” in
2014
Earlier work this paper cites.
X. Fan, Z. Liu, and G. Sun, “Salient region detection for stereoscopic images,” in
2014
Earlier work this paper cites.
S. Gupta, R. Girshick, P. Arbeláez, and J. Malik, “Learning rich features from RGB-D images for object detection and segmentation,” in
2014
Earlier work this paper cites.
Y. Li, X. Hou, C. Koch, J. M. Rehg, and A. L. Yuille, “The secrets of salient object segmentation,” in
2014
Earlier work this paper cites.
H. Fu, D. Xu, S. Lin, and J. Liu, “Object-based rgbd image co-segmentation with mutex constraint,” in
2015
Earlier work this paper cites.
A. Borji, M.-M. Cheng, H. Jiang, and J. Li, “Salient Object Detection: A Benchmark,”
2015
Earlier work this paper cites.
D. Tao, J. Cheng, M. Song, and X. Lin, “Manifold ranking-based matrix factorization for saliency detection,”
2015
Earlier work this paper cites.
R. Zhao, W. Ouyang, H. Li, and X. Wang, “Saliency detection by multi-context deep learning,” in
2015
Earlier work this paper cites.
J. Ren, X. Gong, L. Yu, W. Zhou, and M. Ying Yang, “Exploiting Global Priors for RGB-D Saliency Detection,” in
2015
Earlier work this paper cites.
M.-M. Cheng, N. J. Mitra, X. Huang, P. H. S. Torr, and S.-M. Hu, “Global contrast based salient region detection,”
2015
Earlier work this paper cites.
G. Li and Y. Yu, “Visual saliency based on multiscale deep features,” in
2015
Earlier work this paper cites.
K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” in
2015
Earlier work this paper cites.
T. Chen, L. Lin, L. Liu, X. Luo, and X. Li, “DISC: Deep Image Saliency Computing via Progressive Representation Learning.”
2016
Earlier work this paper cites.
G. Lee, Y.-W. Tai, and J. Kim, “Deep saliency with encoded low level distance map and high level features,” in
2016
Earlier work this paper cites.
D. Feng, N. Barnes, S. You, and C. McCarthy, “Local background enclosure for RGB-D salient object detection,” in
2016
Earlier work this paper cites.
J. Guo, T. Ren, and J. Bei, “Salient object detection for rgb-d image via saliency evolution,” in
2016
Earlier work this paper cites.
R. Cong, J. Lei, C. Zhang, Q. Huang, X. Cao, and C. Hou, “Saliency detection for stereoscopic images based on depth confidence analysis and multiple cues fusion,”
2016
Earlier work this paper cites.
H. Du, Z. Liu, H. Song, L. Mei, and Z. Xu, “Improving rgbd saliency detection using progressive region classification and saliency fusion,”
2016
Earlier work this paper cites.
X. Yang, T. Mei, Y.-Q. Xu, Y. Rui, and S. Li, “Automatic generation of visual-textual presentation layout,”
2016
Cited alongside, same era.
J. Yu, B. Zhang, Z. Kuang, D. Lin, and J. Fan, “iprivacy: image privacy protection by identifying sensitive objects via deep multi-task learning,”
2016
Cited alongside, same era.
G. Li, Y. Xie, L. Lin, and Y. Yu, “Instance-level salient object segmentation,” in
2017
Cited alongside, same era.
M. A. Islam, M. Kalash, M. Rochan, N. Bruce, and Y. Wang, “Salient object detection using a context-aware refinement network,” in
2017
Cited alongside, same era.
Z. Luo, A. Mishra, A. Achkar, J. Eichel, S. Li, and P.-M. Jodoin, “Non-local deep features for salient object detection,” in
2017
Cited alongside, same era.
D.-P. Fan, J.-J. Liu, S.-H. Gao, Q. Hou, A. Borji, and M.-M. Cheng, “Salient objects in clutter: Bringing salient object detection to the foreground,” in
2018
Later among the works it cites.
M. Sandler, A. Howard, M. Zhu, A. Zhmoginov, and L.-C. Chen, “Mobilenetv2: Inverted residuals and linear bottlenecks,” in
2018
Later among the works it cites.
J. Zhang, J. Yu, and D. Tao, “Local deep-feature alignment for unsupervised dimension reduction,”
2018
Later among the works it cites.
A. Borji, M.-M. Cheng, Q. Hou, H. Jiang, and J. Li, “Salient object detection: A survey,”
2019
Closest in time.
P. Zhang, W. Liu, H. Lu, and C. Shen, “Salient object detection with lossless feature reflection and weighted structural loss,”
2019
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X. Huang and Y.-J. Zhang, “300-fps salient object detection via minimum directional contrast,”
2017
Cited alongside, same era.
X. Chen, A. Zheng, J. Li, and F. Lu, “Look, perceive and segment: Finding the salient objects in images via two-stream fixation-semantic cnns,” in
2017
Cited alongside, same era.
L. Qu, S. He, J. Zhang, J. Tian, Y. Tang, and Q. Yang, “RGBD salient object detection via deep fusion,”
2017
Cited alongside, same era.
H. Song, Z. Liu, H. Du, G. Sun, O. Le Meur, and T. Ren, “Depth-aware salient object detection and segmentation via multiscale discriminative saliency fusion and bootstrap learning,”
2017
Cited alongside, same era.
C. Zhu, G. Li, W. Wang, and R. Wang, “An innovative salient object detection using center-dark channel prior,” in
2017
Cited alongside, same era.
W. Wang, J. Shen, Y. Yu, and K.-L. Ma, “Stereoscopic thumbnail creation via efficient stereo saliency detection,”
2017
Cited alongside, same era.
D.-P. Fan, M.-M. Cheng, Y. Liu, T. Li, and A. Borji, “Structure-measure: A new way to evaluate foreground maps,” in
2017
Cited alongside, same era.
W. Wang, J. Shen, J. Xie, M.-M. Cheng, H. Ling, and A. Borji, “Revisiting video saliency prediction in the deep learning era,”
2019
Closest in time.
D.-P. Fan, W. Wang, M.-M. Cheng, and J. Shen, “Shifting more attention to video salient object detection,” in
2019
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Y. Zeng, Y. Zhuge, H. Lu, and L. Zhang, “Multi-source weak supervision for saliency detection,” in
2019
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R. Wu, M. Feng, W. Guan, and D. Wang, “A mutual learning method for salient object detection with intertwined multi-supervision,” in
2019
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L. Zhang, i. JZhang, Z. Lin, H. Lu, and Y. He, “Capsal: Leveraging captioning to boost semantics for salient object detection,” in
2019
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M. Feng, H. Lu, and E. Ding, “Attentive feedback network for boundary-aware salient object detection,” in
2019
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Y. Xu, X. Hong, F. Porikli, X. Liu, J. Chen, and G. Zhao, “Saliency integration: An arbitrator model,”
2019
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Q. Hou, M.-M. Cheng, X. Hu, A. Borji, Z. Tu, and P. Torr, “Deeply supervised salient object detection with short connections,”
2019
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Y. Zhuge, Y. Zeng, and H. Lu, “Deep embedding features for salient object detection,” in
2019
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2019
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S. Jia and N. D. Bruce, “Richer and deeper supervision network for salient object detection,”
2019
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C. Zhu, X. Cai, K. Huang, T. H. Li, and G. Li, “Pdnet: Prior-model guided depth-enhanced network for salient object detection,” in
2019
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J.-X. Zhao, Y. Cao, D.-P. Fan, M.-M. Cheng, X.-Y. Li, and L. Zhang, “Contrast prior and fluid pyramid integration for rgbd salient object detection,” in
2019
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N. Wang and X. Gong, “Adaptive Fusion for RGB-D Salient Object Detection,”
2019
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H. Chen, Y. Li, and D. Su, “Multi-modal fusion network with multi-scale multi-path and cross-modal interactions for RGB-D salient object detection,”
2019
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H. Chen and Y. Li, “Three-stream attention-aware network for RGB-D salient object detection,”
2019
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A. Kirillov, R. Girshick, K. He, and P. Dollár, “Panoptic feature pyramid networks,” in
2019
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Y. Xiong, R. Liao, H. Zhao, R. Hu, M. Bai, E. Yumer, and R. Urtasun, “Upsnet: A unified panoptic segmentation network,” in
2019
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T. Zhao and X. Wu, “Pyramid feature attention network for saliency detection,” in
2019
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S. Mehta, M. Rastegari, L. Shapiro, and H. Hajishirzi, “Espnetv2: A light-weight, power efficient, and general purpose convolutional neural network,”
2019
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G.-Y. Nie, M.-M. Cheng, Y. Liu, Z. Liang, D.-P. Fan, Y. Liu, and Y. Wang, “Multi-level context ultra-aggregation for stereo matching,” in
2019
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J. Shen, X. Dong, J. Peng, X. Jin, L. Shao, and F. Porikli, “Submodular function optimization for motion clustering and image segmentation,”
2019
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J. Yu, C. Zhu, J. Zhang, Q. Huang, and D. Tao, “Spatial pyramid-enhanced netvlad with weighted triplet loss for place recognition,”
2019
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J. Yu, M. Tan, H. Zhang, D. Tao, and Y. Rui, “Hierarchical deep click feature prediction for fine-grained image recognition,”
2019
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S. He, C. Han, G. Han, and J. Qin, “Exploring duality in visual question-driven top-down saliency,”
2019
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Y. Piao, W. Ji, J. Li, M. Zhang, and H. Lu, “Depth-induced multi-scale recurrent attention network for saliency detection,” in
2019
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2019
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S.-H. Gao, M.-M. Cheng, K. Zhao, X.-Y. Zhang, M.-H. Yang, and P. Torr, “Res2net: A new multi-scale backbone architecture,”
2020
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D.-P. Fan, G.-P. Ji, G. Sun, M.-M. Cheng, J. Shen, and L. Shao, “Camouflaged object detection,” in
2020
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D.-P. Fan, T. Zhou, G.-P. Ji, Y. Zhou, G. Chen, H. Fu, J. Shen, and L. Shao, “Inf-net: Automatic covid-19 lung infection segmentation from ct scans,”
2020
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J. Zhang, D.-P. Fan, Y. Dai, S. Anwar, F. Sadat Saleh, T. Zhang, and N. Barnes, “UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders,” in
2020
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K. F. Fu, D.-P. Fan, G.-P. Ji, and Q. Zhao, “JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detection,” in
2020
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Z. Liu, W. Zhang, and P. Zhao, “A Cross-modal Adaptive Gated Fusion Generative Adversarial Network for RGB-D Salient Object Detection,”
2020
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Y. Piao, Z. Rong, M. Zhang, and H. Lu, “Exploit and Replace: An Asymmetrical Two-Stream Architecture for Versatile Light Field Saliency Detection,” in
2020
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X. Chen, R. Girshick, K. He, and P. Dollár, “Tensormask: A foundation for dense object segmentation,” in
2069
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