30 citations · 43 across the 6 of their papers we have counts for
6 papers
Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola +3
With the recent surge in popularity of AR/VR applications, realistic and accurate control of 3D full-body avatars has become a highly demanded feature. A particular challenge is th…
Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers
Robin Kips, Ruowei Jiang, Sileye Ba +4
Augmented reality applications have rapidly spread across online platforms, allowing consumers to virtually try-on a variety of products, such as makeup, hair dying, or shoes. Howe…
Hair Color Digitization through Imaging and Deep Inverse Graphics
Robin Kips, Panagiotis-Alexandros Bokaris, Matthieu Perrot +2
Hair appearance is a complex phenomenon due to hair geometry and how the light bounces on different hair fibers. For this reason, reproducing a specific hair color in a rendering e…
Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example
Robin Kips, Ruowei Jiang, Sileye Ba +5
While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task. I…
Learning Long-Term Style-Preserving Blind Video Temporal Consistency
Hugo Thimonier, Julien Despois, Robin Kips +1
When trying to independently apply image-trained algorithms to successive frames in videos, noxious flickering tends to appear. State-of-the-art post-processing techniques that aim…
CA-GAN: Weakly Supervised Color Aware GAN for Controllable Makeup Transfer
Robin Kips, Pietro Gori, Matthieu Perrot +1
While existing makeup style transfer models perform an image synthesis whose results cannot be explicitly controlled, the ability to modify makeup color continuously is a desirable…