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End-to-End Reconstruction-Classification Learning for Face Forgery Detection
Computer Vision and Pattern Recognition, 2022Existing face forgery detectors mainly focus on specific forgery patterns like noise characteristics, local textures, or frequency statistics for forgery detection. This causes specialization of learned representations to known forgery patterns presented
Junyi Cao +5 more
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Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues
European Conference on Computer Vision, 2020As realistic facial manipulation technologies have achieved remarkable progress, social concerns about potential malicious abuse of these technologies bring out an emerging research topic of face forgery detection.
Yuyang Qian +4 more
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International Journal of Engineering Applied Sciences and Technology, 2023
In the digital age, the ability to manipulate digital images has become increasingly sophisticated, making it challenging to detect and distinguish between authentic and forged images. Image forgery detection is an active and crucial area of research, with various methods and techniques being proposed to detect manipulated images. This paper provides a
Shivam Pandey +3 more
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In the digital age, the ability to manipulate digital images has become increasingly sophisticated, making it challenging to detect and distinguish between authentic and forged images. Image forgery detection is an active and crucial area of research, with various methods and techniques being proposed to detect manipulated images. This paper provides a
Shivam Pandey +3 more
+4 more sources
FORGERY DETECTION BY LOCAL CORRESPONDENCE
International Journal of Pattern Recognition and Artificial Intelligence, 2001Signatures may be stylish or unconventional and have many personal characteristics that are challenging to reproduce by anyone other than the original author. For this reason, signatures are used and accepted as proof of authorship or consent on personal checks, credit purchases and legal documents. Currently signatures are verified only informally in
Jinhong Katherine Guo +2 more
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On the Generality of Facial Forgery Detection
2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems Workshops (MASSW), 2019A variety of architectures have been designed or repurposed for the task of facial forgery detection. While many of these designs have seen great success, they largely fail to address challenges these models may face in practice. A major challenge is posed by generality, wherein models must be prepared to perform in a variety of domains. In this paper,
Joshua Brockschmidt +2 more
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Computer Detection of Freehand Forgeries
IEEE Transactions on Computers, 1977This paper deals with the detection of freehand forgeries of signatures on bank checks. The detection process makes use of size ratio and slant features derived from Eden's kinematic stroke model for handwriting, which was modified to make it applicable to prewritten material.
Roger N. Nagel, Azriel Rosenfeld
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Automatic detection of handwriting forgery
Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition, 2003We investigated the detection of handwriting forgery by both human and machine. We obtained experimental handwriting data from subjects writing samples in their natural style and writing forgeries of other subjects' handwriting. These handwriting samples were digitally scanned and stored in an image database.
Sung-Hyuk Cha, Charles C. Tappert
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Forensics Adapter: Adapting CLIP for Generalizable Face Forgery Detection
Computer Vision and Pattern RecognitionWe describe the Forensics Adapter, an adapter network designed to transform CLIP into an effective and generalizable face forgery detector. Although CLIP is highly versatile, adapting it for face forgery detection is nontrivial as forgery-related ...
Xinjie Cui +4 more
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IEEE Signal Processing Magazine, 2009
We are undoubtedly living in an age where we are exposed to a remarkable array of visual imagery. While we may have historically had confidence in the integrity of this imagery, today's digital technology has begun to erode this trust. From the tabloid magazines to the fashion industry and in mainstream media outlets, scientific journals, political ...
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We are undoubtedly living in an age where we are exposed to a remarkable array of visual imagery. While we may have historically had confidence in the integrity of this imagery, today's digital technology has begun to erode this trust. From the tabloid magazines to the fashion industry and in mainstream media outlets, scientific journals, political ...
openaire +1 more source
Forgery-Aware Adaptive Learning With Vision Transformer for Generalized Face Forgery Detection
IEEE transactions on circuits and systems for video technology (Print)With the rapid progress of generative models, the current challenge in face forgery detection is how to effectively detect realistic manipulated faces from different unseen domains.
Anwei Luo +6 more
semanticscholar +1 more source