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Multi-Tool Image Editing Attribution in Facial Forgery

Paper recorded by Signals 4 on 2026-09-02 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-02 on arXiv · recorded by Signals 4 on 2026-09-03

Category: cs.CV · 计算机视觉 · first seen 2026-09-03

Abstract

As generative AI tools become increasingly powerful and easy to use, people can easily edit portrait images with a prompt, necessitating the task of image editing attribution, which predicts the involved editing tools from the given image. Existing attribution methods hold the single-tool assumption and can only attribute a specific editing tool, but struggle to handle the more complex and increas

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#168 most recent of 237 cs.CV papers we have recorded · ↑ newer: Video-Based Palm-Vein Authentication under Challenging Conditions · ↓ older: Balancing Frequencies and Pixels in Flow Matching
Cite this page: Multi-Tool Image Editing Attribution in Facial Forgery: the #168 most recent of 237 cs.CV papers we have recorded (as of 2026-09-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/multi-tool-image-editing-attribution-in-facial-forgery.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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