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Memory-oriented Decoder for Light Field Salient Object Detection
Miao Zhang · Jingjing Li · Wei Ji · Yongri Piao · Huchuan Lu

Wed Dec 11 10:45 AM -- 12:45 PM (PST) @ East Exhibition Hall B + C #79

Light field data have been demonstrated in favor of many tasks in computer vision, but existing works about light field saliency detection still rely on hand-crafted features. In this paper, we present a deep-learning-based method where a novel memory-oriented decoder is tailored for light field saliency detection. Our goal is to deeply explore and comprehensively exploit internal correlation of focal slices for accurate prediction by designing feature fusion and integration mechanisms. The success of our method is demonstrated by achieving the state of the art on three datasets. We present this problem in a way that is accessible to members of the community and provide a large-scale light field dataset that facilitates comparisons across algorithms. The code and dataset will be made publicly available.

Author Information

Miao Zhang (Dalian University of Technology)
Jingjing Li (Dalian University of Technology)
Wei Ji (Dalian University of Technology)
Yongri Piao (Dalian University of Technology)
Huchuan Lu (Dalian University of Technology)

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