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Seung-hyeok Back

4 accepted papers

2026

DeepProtect: Proactive Face-Swapping Defense using Identity Blending and Attribute Distortion

CVPR 2026

Face-swapping deepfakes allow realistic identity transfer, which can serve creative purposes but increases the risk of identity abuse. A proactive defense aims to prevent deepfake creation by obstructing identity feature extraction from input images, essential for identity-driven face-swapping. Exis

Cited by 0SourcecodeScholar
2026

Latent-RAG: Identity Retrieval-Guided Latent Augmentation for Privacy-Preserving Person Re-Identification

ICRA 2026poster

Person re-identification (re-ID) is crucial for security applications, including autonomous robots that monitor individuals via continuous image acquisition. Such data are transmitted to a database; however, if stored without adequate protection, they can be intercepted, posing privacy risks. In res…

Cited by 0codeScholar
2026

MonoPure: Multi-Component Purification via Disentangled, Projective Representations for Monocular 3D Object Detection

IJCAI 2026

Monocular 3D object detection is a cost-efficient alternative to multisensor systems, yet it remains fragile to multi-component adversarial attacks that perturb the image and tamper with camera calibration. Compounded distortions degrade 3D reasoning by disrupting the correspondence between the 3D g

Cited by 0Scholar
2026

Robust, Generalizable Proactive Face-swapping Defense via Semantic Gradient Divergence

IJCAI 2026

The rapid progress of identity-feature-based face-swapping technology has raised concerns about impersonation and privacy violations. Although proactive defenses aim to block identity extraction at the source, existing methods suffer from perceptible visual artifacts, poor generalization across dive

Cited by 0Scholar