31 citations · 34 across the 9 of their papers we have counts for
9 papers
Head Avatars with Dynamic Explicit Hair
Vanessa Sklyarova, Haonan Chen, Berna Kabadayi +8
We present DynHair, a novel method for tracking and modeling dynamic hair for human head avatars. From video input, we reconstruct a dynamic head avatar with an explicit strand-bas…
Human Hair Reconstruction with Strand-Aligned 3D Gaussians
Egor Zakharov, Vanessa Sklyarova, Michael Black +3
We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians to produce accurate and realistic strand-based reconstructions fr…
Gaussian Garments: Reconstructing Simulation-Ready Clothing with Photorealistic Appearance from Multi-View Video
Boxiang Rong, Artur Grigorev, Wenbo Wang +4
We introduce Gaussian Garments, a novel approach for reconstructing realistic simulation-ready garment assets from multi-view videos. Our method represents garments with a combinat…
RILe: Reinforced Imitation Learning
Mert Albaba, Sammy Christen, Thomas Langarek +3
Acquiring complex behaviors is essential for artificially intelligent agents, yet learning these behaviors in high-dimensional settings poses a significant challenge due to the vas…
HMP: Hand Motion Priors for Pose and Shape Estimation from Video
Enes Duran, Muhammed Kocabas, Vasileios Choutas +2
Understanding how humans interact with the world necessitates accurate 3D hand pose estimation, a task complicated by the hand's high degree of articulation, frequent occlusions, s…
HAAR: Text-Conditioned Generative Model of 3D Strand-based Human Hairstyles
Vanessa Sklyarova, Egor Zakharov, Otmar Hilliges +2
We present HAAR, a new strand-based generative model for 3D human hairstyles. Specifically, based on textual inputs, HAAR produces 3D hairstyles that could be used as production-le…
HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video
Zicong Fan, Maria Parelli, Maria Eleni Kadoglou +4
Since humans interact with diverse objects every day, the holistic 3D capture of these interactions is important to understand and model human behaviour. However, most existing met…
FLARE: Fast Learning of Animatable and Relightable Mesh Avatars
Shrisha Bharadwaj, Yufeng Zheng, Otmar Hilliges +2
Our goal is to efficiently learn personalized animatable 3D head avatars from videos that are geometrically accurate, realistic, relightable, and compatible with current rendering…
PACE: Human and Camera Motion Estimation from in-the-wild Videos
Muhammed Kocabas, Ye Yuan, Pavlo Molchanov +5
We present a method to estimate human motion in a global scene from moving cameras. This is a highly challenging task due to the coupling of human and camera motions in the video.…