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LPCLNet: Leveraging local pixel-wise contrastive learning for image tampering localization | Synapse
March 3, 2026
LPCLNet: Leveraging local pixel-wise contrastive learning for image tampering localization
JS
Jun Sang
XC
Xiaowen Chen
WG
Wenhui Gong
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Key Points
Image tampering localization improves significantly using the proposed algorithm, enhancing detection accuracy.
Key metrics show an increase in localization performance, with a notable improvement over existing methods.
Assessments using the LPCLNet approach highlight the effectiveness of local pixel-wise contrastive learning in image detection.
Results emphasize the need for advanced techniques in digital forensics, particularly for real-world applications.
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Sang et al. (Fri,) studied this question.
synapsesocial.com/papers/69a768a3badf0bb9e87e56c7
https://doi.org/https://doi.org/10.1016/j.ins.2026.123205