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cs.CV2026
Efficient Document Tampering Localization with Multi-Level Discrepancy Features and Unified DCT-Quantization Embedding
Mohamed Dhouib, Ye Zhu, Sonia Vanier +1
Localizing document tampering is extremely challenging, as manipulations are crafted to appear visually consistent and often leave only subtle traces that are nearly invisible to t…
cs.CV2026
Leveraging Contrastive Learning for a Similarity-Guided Tampered Document Data Generation Pipeline
Mohamed Dhouib, Davide Buscaldi, Sonia Vanier +1
Detecting tampered text in document images is a challenging task due to data scarcity. To address this, previous work has attempted to generate tampered documents using rule-based…