SDeMorph: Towards Better Facial De-morphing from Single Morph
Face Recognition Systems (FRS) are vulnerable to morph attacks. A face morph is created by combining multiple identities with the intention to fool FRS and making it match the morph with multiple identities. Current Morph Attack Detection (MAD) can detect the morph but are unable to recover the identities used to create the morph with satisfactory outcomes. Existing work in de-morphing is mostly reference-based, i.e. they require the availability of one identity to recover the other. Sudipta et al. \cite{ref9} proposed a reference-free de-morphing technique but the visual realism of outputs produced were feeble. In this work, we propose SDeMorph (Stably Diffused De-morpher), a novel de-morphing method that is reference-free and recovers the identities of bona fides. Our method produces feature-rich outputs that are of significantly high quality in terms of definition and facial fidelity. Our method utilizes Denoising Diffusion Probabilistic Models (DDPM) by destroying the input morphed signal and then reconstructing it back using a branched-UNet. Experiments on ASML, FRLL-FaceMorph, FRLL-MorDIFF, and SMDD datasets support the effectiveness of the proposed method.
Code (0)
등록된 구현이 없습니다.
Tasks
DenoisingFace RecognitionMORPHMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
dc-GAN: Dual-Conditioned GAN for Face Demorphing From a Single Morph
A facial morph is an image created by combining two face images pertaining to two distinct identities. Face demorphing inverts the process and tries to recover the original images constituting a facial morph. While morph…
MORPHFD-GAN: Face-demorphing generative adversarial network for restoring accomplice's facial image
Face morphing attack is proved to be a serious threat to the existing face recognition systems. Although a few face morphing detection methods have been put forward, the face morphing accomplice's facial restoration rema…
Face RecognitionGenerative Adversarial NetworkFacial De-morphing: Extracting Component Faces from a Single Morph
A face morph is created by strategically combining two or more face images corresponding to multiple identities. The intention is for the morphed image to match with multiple identities. Current morph attack detection st…
Generative Adversarial NetworkMORPHOptimal-Landmark-Guided Image Blending for Face Morphing Attacks
In this paper, we propose a novel approach for conducting face morphing attacks, which utilizes optimal-landmark-guided image blending. Current face morphing attacks can be categorized into landmark-based and generation-…
Face RecognitionEnhancing Single-Image Facial Demorphing using Multimodal Large Language Models
Face recognition systems are increasingly vulnerable to morphing attacks, where a composite image is crafted to match multiple identities, enabling unauthorized access and identity fraud. Existing detection methods ident…
Face RecognitionText Generation