Cross-modal learning for saliency prediction in mobile environment
Author:
Affiliation:
1. Beijing University of Posts and Telecommunications, Beijing, China
2. Xinyang Vocational and Technical College, Xinyang, China
3. Huazhong University of Science and Technology, Wuhan, China
Funder
Beijing Nova Program from Beijing Municipal Science and Technology Commission
Natural Science Foundation of China
Major Scientific and Technological Project of Hubei Province
National Key Research and Development Program of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3444685.3446304
Reference43 articles.
1. Spatio-Temporal Saliency Networks for Dynamic Saliency Prediction
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3. N. Bruce C. Catton and S. Janjic. 2016. A deeper look at saliency: Feature contrast semantics and beyond. In CVPR. 516--524. N. Bruce C. Catton and S. Janjic. 2016. A deeper look at saliency: Feature contrast semantics and beyond. In CVPR. 516--524.
4. N. Bruce and K. Tsotsos. 2005. Saliency based on information maximization. In NIPS. 155--162. N. Bruce and K. Tsotsos. 2005. Saliency based on information maximization. In NIPS. 155--162.
5. J. Chen Y. Li Y. Fan W. Wu X. Wang H. Cao and Y. Chen. 2016. Investigation of mobile surroundings for visual attention based on image perception model. In VCIP. 1--4. J. Chen Y. Li Y. Fan W. Wu X. Wang H. Cao and Y. Chen. 2016. Investigation of mobile surroundings for visual attention based on image perception model. In VCIP. 1--4.
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