papers

Publications (10)

cs.CV2021

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…

cs.CV2020

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…

cs.CV2025

From Sparse Signal to Smooth Motion: Real-Time Motion Generation with Rolling Prediction Models

German Barquero, Nadine Bertsch, Manojkumar Marramreddy +8

In extended reality (XR), generating full-body motion of the users is important to understand their actions, drive their virtual avatars for social interaction, and convey a realis…

cs.CV2023

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…

cs.GR2022

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…

cs.CV2021

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…

cs.CV2024

XR-MBT: Multi-modal Full Body Tracking for XR through Self-Supervision with Learned Depth Point Cloud Registration

Denys Rozumnyi, Nadine Bertsch, Othman Sbai +6

Tracking the full body motions of users in XR (AR/VR) devices is a fundamental challenge to bring a sense of authentic social presence. Due to the absence of dedicated leg sensors,…

cs.CV2026

EgoExoMoCap: Distributed Ego-Exo Human Motion Capture

Jiaxi Jiang, Bharat Lal Bhatnagar, Nan Yang +6

Human motion capture from head-mounted devices (HMDs) offers a scalable way to acquire real-world human motion and interaction data, which is crucial for applications in embodied A…

cs.CV2022

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…

cs.CV2026

EgoPoseFormer v2: Accurate Egocentric Human Motion Estimation for AR/VR

Zhenyu Li, Sai Kumar Dwivedi, Filip Maric +11

Egocentric human motion estimation is essential for AR/VR experiences, yet remains challenging due to limited body coverage from the egocentric viewpoint, frequent occlusions, and…