3 citations · 3 across the 4 of their papers we have counts for
6 papers
Few-Shot Multi-Human Neural Rendering Using Geometry Constraints
Qian li, Victoria Fernàndez Abrevaya, Franck Multon +1
We present a method for recovering the shape and radiance of a scene consisting of multiple people given solely a few images. Multi-human scenes are complex due to additional occlu…
LEAD: Latent Realignment for Human Motion Diffusion
Nefeli Andreou, Xi Wang, Victoria Fernández Abrevaya +3
Our goal is to generate realistic human motion from natural language. Modern methods often face a trade-off between model expressiveness and text-to-motion alignment. Some align te…
SPARK: Self-supervised Personalized Real-time Monocular Face Capture
Kelian Baert, Shrisha Bharadwaj, Fabien Castan +4
Feedforward monocular face capture methods seek to reconstruct posed faces from a single image of a person. Current state of the art approaches have the ability to regress parametr…
Analysis of Classifier-Free Guidance Weight Schedulers
Xi Wang, Nicolas Dufour, Nefeli Andreou +4
Classifier-Free Guidance (CFG) enhances the quality and condition adherence of text-to-image diffusion models. It operates by combining the conditional and unconditional prediction…
Cross-modal Deep Face Normals with Deactivable Skip Connections
Victoria Fernandez Abrevaya, Adnane Boukhayma, Philip H. S. Torr +1
We present an approach for estimating surface normals from in-the-wild color images of faces. While data-driven strategies have been proposed for single face images, limited availa…
A Decoupled 3D Facial Shape Model by Adversarial Training
Victoria Fernandez Abrevaya, Adnane Boukhayma, Stefanie Wuhrer +1
Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations. A desirable property of these models is their abili…