文章目录
- 引言
- 文献中34中算法对比:
- 34个算法文献名:
-
- 1 WPL
- 2 PCSD
- 3 IPCS
- 4 CBCS
- 5 MI
- 6 CSHS
- 7 ESMG
- 8 BR
- 9 SACS
- 10 DIM
- 11 CODW
- 12 SP-MIL
- 13 GD
- 14 MVSRCC
- 15 UMLF
- 16 DML
- 17 DWSI
- 18 GONet
- 19 COC
- 20 FASS
- 21 PJO
- 22 SPIG
- 23 QGF
- 24 EHL
- 25 IML
- 26 DGFC
- 27 RCANet
- 28 GS
- 29 MGCNet
- 30 MGLCN
- 31 HC
- 32 CSMG
- 33 DeepCO
- 34 GWD
引言
内容引用自 Taking a Deeper Look at Co-Salient Object Detection (2020)
论文开源地址
Ps:先存一下,有时间再一篇一篇系统看,现在一般在看近三年的东西
文献中34中算法对比:
34个算法文献名:
Ps: 1…i…n 对应上图中的顺序
1 WPL
David E Jacobs, Dan B Goldman, and Eli Shechtman. Cosaliency: Where people look when comparing images. In
ACM UIST, pages 219–228, 2010.
2 PCSD
Hwann-Tzong Chen. Preattentive co-saliency detection. In
IEEE ICIP, pages 1117–1120, 2010.
3 IPCS
Hongliang Li and King Ngi Ngan. A co-saliency model of
image pairs. IEEE TIP, 20(12):3365–3375, 2011.
4 CBCS
Huazhu Fu, Xiaochun Cao, and Zhuowen Tu. Cluster-based
co-saliency detection. IEEE TIP, 22(10):3766–3778, 2013.
5 MI
Hongliang Li, Fanman Meng, and King Ngi Ngan. Cosalient object detection from multiple images. IEEE TMM,
15(8):1896–1909, 2013.
6 CSHS
Zhi Liu, Wenbin Zou, Lina Li, Liquan Shen, and Olivier
Le Meur. Co-saliency detection based on hierarchical segmentation. IEEE SPL, 21(1):88–92, 2013.
7 ESMG
Yijun Li, Keren Fu, Zhi Liu, and Jie Yang. Efficient
saliency-model-guided visual co-saliency detection. IEEE
SPL, 22(5):588–592, 2014.
8 BR
Xiaochun Cao, Yupeng Cheng, Zhiqiang Tao, and Huazhu
Fu. Co-saliency detection via base reconstruction. In ACM
MM, pages 997–1000, 2014.
9 SACS
Xiaochun Cao, Zhiqiang Tao, Bao Zhang, Huazhu Fu, and
Wei Feng. Self-adaptively weighted co-saliency detection
via rank constraint. IEEE TIP, 23(9):4175–4186, 2014.
10 DIM
Dingwen Zhang, Junwei Han, Jungong Han, and Ling
Shao. Cosaliency detection based on intrasaliency prior
transfer and deep intersaliency mining. IEEE TNNLS,
27(6):1163–1176, 2015.
11 CODW
Dingwen Zhang, Junwei Han, Chao Li, Jingdong Wang,
and Xuelong Li. Detection of co-salient objects by looking deep and wide. IJCV, 120(2):215–232, 2016.
12 SP-MIL
Dingwen Zhang, Deyu Meng, and Junwei Han. Co-saliency
detection via a self-paced multiple-instance learning framework. IEEE TPAMI, 39(5):865–878, 2016.
13 GD
Lina Wei, Shanshan Zhao, Omar El Farouk Bourahla, Xi
Li, and Fei Wu. Group-wise deep co-saliency detection. In
IJCAI, 2017.
14 MVSRCC
Xiwen Yao, Junwei Han, Dingwen Zhang, and Feiping Nie.
Revisiting co-saliency detection: A novel approach based
on two-stage multi-view spectral rotation co-clustering.
IEEE TIP, 26(7):3196–3209, 2017.
15 UMLF
Junwei Han, Gong Cheng, Zhenpeng Li, and Dingwen
Zhang. A unified metric learning-based framework for cosaliency detection. IEEE TCSVT, 28(10):2473–2483, 2017.
16 DML
Min Li, Shizhong Dong, Kun Zhang, Zhifan Gao, Xi Wu,
Heye Zhang, Guang Yang, and Shuo Li. Deep learning
intra-image and inter-images features for co-saliency detection. In BMVC, page 291, 2018.
17 DWSI
Hongkai Yu, Kang Zheng, Jianwu Fang, Hao Guo, Wei
Feng, and Song Wang. Co-saliency detection within a single image. In AAAI, 2018.
18 GONet
Kuang-Jui Hsu, Chung-Chi Tsai, Yen-Yu Lin, Xiaoning
Qian, and Yung-Yu Chuang. Unsupervised CNN-based cosaliency detection with graphical optimization. In ECCV,
pages 485–501. Springer, 2018.
19 COC
Kuang-Jui Hsu, Yen-Yu Lin, and Yung-Yu Chuang. Coattention cnns for unsupervised object co-segmentation. In
IJCAI, pages 748–756, 2018.
20 FASS
Xiaoju Zheng, Zheng-Jun Zha, and Liansheng Zhuang.
A feature-adaptive semi-supervised framework for cosaliency detection. In ACM MM, pages 959–966, 2018.
21 PJO
Chung-Chi Tsai, Weizhi Li, Kuang-Jui Hsu, Xiaoning
Qian, and Yen-Yu Lin. Image co-saliency detection and
co-segmentation via progressive joint optimization. IEEE
TIP, 28(1):56–71, 2018.
22 SPIG
Dong-ju Jeong, Insung Hwang, and Nam Ik Cho. Cosalient object detection based on deep saliency networks
and seed propagation over an integrated graph. IEEE TIP,
27(12):5866–5879, 2018.
23 QGF
Koteswar Rao Jerripothula, Jianfei Cai, and Junsong Yuan.
Quality-guided fusion-based co-saliency estimation for image co-segmentation and colocalization. IEEE TMM,
20(9):2466–2477, 2018.
24 EHL
Shaoyue Song, Hongkai Yu, Zhenjiang Miao, Dazhou Guo,
Wei Ke, Cong Ma, and Song Wang. An easy-to-hard learning strategy for within-image co-saliency detection. Neurocomputing, 358:166–176, 2019.
25 IML
Jingru Ren, Zhi Liu, Xiaofei Zhou, Cong Bai, and Guangling Sun. Co-saliency detection via integration of multilayer convolutional features and inter-image propagation.
Neurocomputing, 371:137–146, 2020.
26 DGFC
Lina Wei, Shanshan Zhao, Omar El Farouk Bourahla, Xi
Li, Fei Wu, and Yueting Zhuang. Deep group-wise fully
convolutional network for co-saliency detection with graph
propagation. IEEE TIP, 28(10):5052–5063, 2019.
27 RCANet
Bo Li, Zhengxing Sun, Lv Tang, Yunhan Sun, and Jinlong Shi. Detecting robust co-saliency with recurrent coattention neural network. In IJCAI, pages 818–825, 2019.
28 GS
Chong Wang, Zheng-Jun Zha, Dong Liu, and Hongtao Xie.
Robust deep co-saliency detection with group semantic. In
AAAI, pages 8917–8924, 2019.
29 MGCNet
Bo Jiang, Xingyue Jiang, Jin Tang, Bin Luo, and Shilei
Huang. Multiple graph convolutional networks for cosaliency detection. In IEEE ICME, pages 332–337, 2019.
30 MGLCN
Bo Jiang, Xingyue Jiang, Ajian Zhou, Jin Tang, and Bin
Luo. A unified multiple graph learning and convolutional
network model for co-saliency estimation. In ACM MM,
pages 1375–1382, 2019.
31 HC
Bo Jiang, Xingyue Jiang, Ajian Zhou, Jin Tang, and Bin
Luo. A unified multiple graph learning and convolutional
network model for co-saliency estimation. In ACM MM,
pages 1375–1382, 2019.
32 CSMG
Kaihua Zhang, Tengpeng Li, Bo Liu, and Qingshan Liu.
Co-saliency detection via mask-guided fully convolutional
networks with multi-scale label smoothing. In CVPR, pages
3095–3104, 2019.
33 DeepCO
Kuang-Jui Hsu, Yen-Yu Lin, and Yung-Yu Chuang.
DeepCO3: Deep Instance Co-Segmentation by Co-Peak
Search and Co-Saliency Detection. In IEEE CVPR, 2019.
34 GWD
Bo Li, Zhengxing Sun, Qian Li, Yunjie Wu, and Anqi Hu.
Group-wise deep object co-segmentation with co-attention
recurrent neural network. In IEEE ICCV, 2019.