activity
20202023
most citedOn the detection of synthetic images generated by diffusion models

10 citations · 31 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20237 cited

Generalizable One-shot Neural Head Avatar

Xueting Li, Shalini De Mello, Sifei Liu +3

We present a method that reconstructs and animates a 3D head avatar from a single-view portrait image. Existing methods either involve time-consuming optimization for a specific pe…

cs.CV20221 cited

RANA: Relightable Articulated Neural Avatars

Umar Iqbal, Akin Caliskan, Koki Nagano +3

We propose RANA, a relightable and articulated neural avatar for the photorealistic synthesis of humans under arbitrary viewpoints, body poses, and lighting. We only require a shor…

cs.CV202210 cited

On the detection of synthetic images generated by diffusion models

Riccardo Corvi, Davide Cozzolino, Giada Zingarini +3

Over the past decade, there has been tremendous progress in creating synthetic media, mainly thanks to the development of powerful methods based on generative adversarial networks…

cs.CV20222 cited

DRaCoN -- Differentiable Rasterization Conditioned Neural Radiance Fields for Articulated Avatars

Amit Raj, Umar Iqbal, Koki Nagano +4

Acquisition and creation of digital human avatars is an important problem with applications to virtual telepresence, gaming, and human modeling. Most contemporary approaches for av…

cs.CV20213 cited

Normalized Avatar Synthesis Using StyleGAN and Perceptual Refinement

Huiwen Luo, Koki Nagano, Han-Wei Kung +6

We introduce a highly robust GAN-based framework for digitizing a normalized 3D avatar of a person from a single unconstrained photo. While the input image can be of a smiling pers…

cs.CV20208 cited

One-Shot Identity-Preserving Portrait Reenactment

Sitao Xiang, Yuming Gu, Pengda Xiang +4

We present a deep learning-based framework for portrait reenactment from a single picture of a target (one-shot) and a video of a driving subject. Existing facial reenactment metho…