PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization
To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations. PSCC-Net processes the image in a two-path procedure: a top-down path that extracts local and...
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| Published in | IEEE transactions on circuits and systems for video technology Vol. 32; no. 11; pp. 7505 - 7517 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.11.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
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| Abstract | To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations. PSCC-Net processes the image in a two-path procedure: a top-down path that extracts local and global features and a bottom-up path that detects whether the input image is manipulated, and estimates its manipulation masks at multiple scales, where each mask is conditioned on the previous one. Different from the conventional encoder-decoder and no-pooling structures, PSCC-Net leverages features at different scales with dense cross-connections to produce manipulation masks in a coarse-to-fine fashion. Moreover, a Spatio-Channel Correlation Module (SCCM) captures both spatial and channel-wise correlations in the bottom-up path, which endows features with holistic cues, enabling the network to cope with a wide range of manipulation attacks. Thanks to the light-weight backbone and progressive mechanism, PSCC-Net can process <inline-formula> <tex-math notation="LaTeX">1,080\text{P} </tex-math></inline-formula> images at 50+FPS. Extensive experiments demonstrate the superiority of PSCC-Net over the state-of-the-art methods on both detection and localization. Codes and models are available at https://github.com/proteus1991/PSCC-Net . |
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| AbstractList | To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations. PSCC-Net processes the image in a two-path procedure: a top-down path that extracts local and global features and a bottom-up path that detects whether the input image is manipulated, and estimates its manipulation masks at multiple scales, where each mask is conditioned on the previous one. Different from the conventional encoder-decoder and no-pooling structures, PSCC-Net leverages features at different scales with dense cross-connections to produce manipulation masks in a coarse-to-fine fashion. Moreover, a Spatio-Channel Correlation Module (SCCM) captures both spatial and channel-wise correlations in the bottom-up path, which endows features with holistic cues, enabling the network to cope with a wide range of manipulation attacks. Thanks to the light-weight backbone and progressive mechanism, PSCC-Net can process [Formula Omitted] images at 50+FPS. Extensive experiments demonstrate the superiority of PSCC-Net over the state-of-the-art methods on both detection and localization. Codes and models are available at https://github.com/proteus1991/PSCC-Net . To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations. PSCC-Net processes the image in a two-path procedure: a top-down path that extracts local and global features and a bottom-up path that detects whether the input image is manipulated, and estimates its manipulation masks at multiple scales, where each mask is conditioned on the previous one. Different from the conventional encoder-decoder and no-pooling structures, PSCC-Net leverages features at different scales with dense cross-connections to produce manipulation masks in a coarse-to-fine fashion. Moreover, a Spatio-Channel Correlation Module (SCCM) captures both spatial and channel-wise correlations in the bottom-up path, which endows features with holistic cues, enabling the network to cope with a wide range of manipulation attacks. Thanks to the light-weight backbone and progressive mechanism, PSCC-Net can process <inline-formula> <tex-math notation="LaTeX">1,080\text{P} </tex-math></inline-formula> images at 50+FPS. Extensive experiments demonstrate the superiority of PSCC-Net over the state-of-the-art methods on both detection and localization. Codes and models are available at https://github.com/proteus1991/PSCC-Net . |
| Author | Liu, Xiaoming Chen, Jun Liu, Yaojie Liu, Xiaohong |
| Author_xml | – sequence: 1 givenname: Xiaohong orcidid: 0000-0001-6377-4730 surname: Liu fullname: Liu, Xiaohong email: xiaohongliu@sjtu.edu.cn organization: Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada – sequence: 2 givenname: Yaojie orcidid: 0000-0003-3756-7820 surname: Liu fullname: Liu, Yaojie email: liuyaoj1@msu.edu organization: Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA – sequence: 3 givenname: Jun orcidid: 0000-0002-8084-9332 surname: Chen fullname: Chen, Jun email: chenjun@mcmaster.ca organization: Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada – sequence: 4 givenname: Xiaoming surname: Liu fullname: Liu, Xiaoming email: liuxm@msu.edu organization: Department of Computer Science and Engineering, Michigan State University, East Lansing, MI, USA |
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| Snippet | To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network... |
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| SubjectTerms | attention mechanism Coders Correlation Encoders-Decoders Estimation Feature extraction Forgery Image manipulation Image manipulation detection and localization Localization Location awareness Masks progressive mechanism Splicing Task analysis Weight reduction |
| Title | PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization |
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