Pengfei Wang, Fan Shi, Xinbo Geng, Xu Cheng, Xinpeng Zhang
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引用次数: 0
Abstract
Recently, light field data has garnered significant attention due to its immense potential in Unsupervised Salient Object Detection (USOD). However, these methods neglect the ability of the light field information itself to generate pseudo-labels. In this paper, we design a two-stage pseudo-label generation framework, based on the data structure of light field. In the first stage, we propose a proxy task called multi-focus image reconstruction (MFIR). It leverages light field information to generate a shallow depth-of-field image with the focus on the salient object, approximating the learning of saliency features. In the second stage, we introduce repair network and prior-guided mask (PGM) to guide pseudo-label updating by leveraging the stability of salient features in pre-trained weights, thereby addressing the depth ambiguity issue arising from MFIR. We name our framework light field refocus for saliency (LFR4S). Additionally, we use the generated pseudo-labels for supervised training and conduct comparative analysis on the results. Experimental results demonstrate that our method surpasses most existing USOD methods across multiple datasets. Finally, we design corresponding ablation studies to verify the necessity of certain modules.
期刊介绍:
Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal.
The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as:
• big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,