The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Context-Aware Saliency Detection
Abstract
We propose a new type of saliency—context-aware saliency—which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological literature. The benefits of the proposed approach are evaluated in two applications where the context of the dominant objects is just as essential as the objects themselves. In image retargeting, we demonstrate that using our saliency prevents distortions in the important regions. In summarization, we show that our saliency helps to produce compact, appealing, and informative summaries.
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Cites
Computational modelling of visual attention
Itti, L., & Koch, C. (2001) · Nature Reviews Neuroscience · doi:10.1038/35058500 · Cited by 4,733
Sampling Strategies for Bag-of-Features Image Classification
Nowak, E., Jurie, F., & Triggs, B. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744085_38 · Cited by 927
Cited by
Structure-Measure: A New Way to Evaluate Foreground Maps
Fan, D.-P., Cheng, M.-M., Liu, Y., Li, T., & Borji, A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.487 · Cited by 2,092
Synthesizing Supervision for Learning Deep Saliency Network without Human Annotation
Zhang, D., Han, J., Zhang, Y., & Xu, D. (2020) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2900649 · Cited by 118
LiveDeep: Online Viewport Prediction for Live Virtual Reality Streaming Using Lifelong Deep Learning
Feng, X., Liu, Y., & Wei, S. (2020) · 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) · doi:10.1109/vr46266.2020.00104 · Cited by 45
Optimization of visual information presentation for visual prosthesis
Guo, F., Yang, Y., & Gao, Y. (2018) · International Journal of Biomedical Imaging · doi:10.1155/2018/3198342 · Cited by 27
Dai, Y., Xue, C., & Zhou, L. (2022) · PLOS ONE · doi:10.1371/journal.pone.0263729 · Cited by 6
Metadata
- Authors
- Goferman, S., Zelnik-Manor, L., & Tal, A.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2012-10
- Volume
- 34
- Issue
- 10
- Pages
- 1915-1926
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W2041719651
- Cited by
- 1,567
- References
- 2
- FWCI
- 62.11
- Type
- journal article
- Language
- en
- Open access
- closed
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- Goferman, S., Zelnik-Manor, L., & Tal, A. (2012). Context-Aware Saliency Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2011.272
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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