Improved Robust Video Saliency Detection based on Long-term Spatial-temporal Information.
Where this comes from
- Record sourced from PubMed, PMID 31449017.
- Also identified by DOI 10.1109/TIP.2019.2934350.
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Abstract
This paper proposes to utilize supervised deep convolutional neural networks to take full advantage of the long-term spatial-temporal information in order to improve the video saliency detection performance. The conventional methods, which use the temporally neighbored frames solely, could easily encounter transient failure cases when the spatial-temporal saliency clues are less-trustworthy for a long period. To tackle the aforementioned limitation, we plan to identify those beyond-scope frames with trustworthy long-term saliency clues first and then align it with the current problem domain for an improved video saliency detection.