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20232025
most citedPrivacy-Preserving Deep Learning Using Deformable Operators for Secure Task Learning

4 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2025

NOWA: Null-space Optical Watermark for Invisible Capture Fingerprinting and Tamper Localization

Edwin Vargas, Jhon Lopez, Henry Arguello +1

Ensuring the authenticity and ownership of digital images is increasingly challenging as modern editing tools enable highly realistic forgeries. Existing image protection systems m…

eess.IV2025

MambaStyle: Efficient StyleGAN Inversion for Real Image Editing with State-Space Models

Jhon Lopez, Carlos Hinojosa, Henry Arguello +1

The task of inverting real images into StyleGAN's latent space to manipulate their attributes has been extensively studied. However, existing GAN inversion methods struggle to bala…

cs.CV2024★ 4 cited

Privacy-Preserving Deep Learning Using Deformable Operators for Secure Task Learning

Fabian Perez, Jhon Lopez, Henry Arguello

In the era of cloud computing and data-driven applications, it is crucial to protect sensitive information to maintain data privacy, ensuring truly reliable systems. As a result, p…

cs.CV2024

Privacy-preserving Optics for Enhancing Protection in Face De-identification

Jhon Lopez, Carlos Hinojosa, Henry Arguello +1

The modern surge in camera usage alongside widespread computer vision technology applications poses significant privacy and security concerns. Current artificial intelligence (AI)…

cs.CV2023

Depth Estimation from a Single Optical Encoded Image using a Learned Colored-Coded Aperture

Jhon Lopez, Edwin Vargas, Henry Arguello

Depth estimation from a single image of a conventional camera is a challenging task since depth cues are lost during the acquisition process. State-of-the-art approaches improve th…