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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.CV2026

NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild

Aleksandr Gushchin, Khaled Abud, Ekaterina Shumitskaya +51

This paper presents an overview of the NTIRE 2026 Challenge on Robust AI-Generated Image Detection in the Wild, held in conjunction with the NTIRE workshop at CVPR 2026. The goal o…

cs.CV2026

FeatDistill: A Feature Distillation Enhanced Multi-Expert Ensemble Framework for Robust AI-generated Image Detection

Zhilin Tu, Kemou Li, Fengpeng Li +3

The rapid iteration and widespread dissemination of deepfake technology have posed severe challenges to information security, making robust and generalizable detection of AI-genera…

cs.CV2025

Structure Disruption: Subverting Malicious Diffusion-Based Inpainting via Self-Attention Query Perturbation

Yuhao He, Jinyu Tian, Haiwei Wu +1

The rapid advancement of diffusion models has enhanced their image inpainting and editing capabilities but also introduced significant societal risks. Adversaries can exploit user…

cs.CV2025

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.CV2025

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…