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20212026
most citedRethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clustering

8 citations · 22 across the 11 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Efficient, Robust, and Anti-Collusion Fingerprinting of Image Diffusion Models

Jianwei Fei, Yunshu Dai, Zhihua Xia +4

Model fingerprinting, embedding user-specific identifiers (fingerprints) into generated outputs, has recently emerged as a popular solution to protect the intellectual property rig…

cs.CV2026

SEED: Simple ViT and Evolving Harness for Explainable Text Forgery Detection

Kahim Wong, Kemou Li, Yiming Chen +2

AI-assisted image editing threatens trust in financial, legal, and identity records. The GenText-Forensics Challenge at ACM MM 2026 addresses this by requiring structured forensic…

cs.CV2023★ 8 cited

Rethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clustering

Haiwei Wu, Yiming Chen, Jiantao Zhou +1

Image forgery detection aims to detect and locate forged regions in an image. Most existing forgery detection algorithms formulate classification problems to classify pixels into f…

cs.CV2023★ 7 cited

Generalizable Synthetic Image Detection via Language-guided Contrastive Learning

Haiwei Wu, Jiantao Zhou, Shile Zhang

The heightened realism of AI-generated images can be attributed to the rapid development of synthetic models, including generative adversarial networks (GANs) and diffusion models…

cs.CV2022★ 7 cited

Exploring Spatial-Temporal Features for Deepfake Detection and Localization

Wu Haiwei, Zhou Jiantao, Zhang Shile +1

With the continuous research on Deepfake forensics, recent studies have attempted to provide the fine-grained localization of forgeries, in addition to the coarse classification at…

cs.CV2021

GIID-Net: Generalizable Image Inpainting Detection via Neural Architecture Search and Attention

Haiwei Wu, Jiantao Zhou

Deep learning (DL) has demonstrated its powerful capabilities in the field of image inpainting, which could produce visually plausible results. Meanwhile, the malicious use of adva…