SPAN: Spatial Pyramid Attention Network forImage Manipulation Localization

• URL: http://arxiv.org/abs/2009.00726v2
• Date: Thu, 14 Jan 2021 01:43:21 GMT
• Title: SPAN: Spatial Pyramid Attention Network forImage Manipulation Localization
• Authors: Xuefeng Hu, Zhihan Zhang, Zhenye Jiang, Syomantak Chaudhuri, Zhenheng Yang, Ram Nevatia
• Abstract summary: We present a novel framework, Spatial Pyramid Attention Network (SPAN) for detection and localization of multiple types of image manipulations. SPAN is trained on a generic, synthetic dataset but can also be fine tuned for specific datasets. The proposed method shows significant gains in performance on standard datasets over previous state-of-the-art methods.
• Score: 24.78951727072683
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a novel framework, Spatial Pyramid Attention Network (SPAN) for detection and localization of multiple types of image manipulations. The proposed architecture efficiently and effectively models the relationship between image patches at multiple scales by constructing a pyramid of local self-attention blocks. The design includes a novel position projection to encode the spatial positions of the patches. SPAN is trained on a generic, synthetic dataset but can also be fine tuned for specific datasets; The proposed method shows significant gains in performance on standard datasets over previous state-of-the-art methods.

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