29 citations · 38 across the 8 of their papers we have counts for
10 papers
ViDS: Video Diffusion Shader using 3D Face Tracking
Wenbo Ji, Davide Davoli, Zhe Chen +3
We introduce ViDS, a Video Diffusion Shader that leverages 3D face tracking for expressive and identity-preserving portrait animation. We first reconstruct the identity-specific 3D…
FactorPortrait: Controllable Portrait Animation via Disentangled Expression, Pose, and Viewpoint
Jiapeng Tang, Kai Li, Chengxiang Yin +8
We introduce FactorPortrait, a video diffusion method for controllable portrait animation that enables lifelike synthesis from disentangled control signals of facial expressions, h…
ROGR: Relightable 3D Objects using Generative Relighting
Jiapeng Tang, Matthew Levine, Dor Verbin +5
We introduce ROGR, a novel approach that reconstructs a relightable 3D model of an object captured from multiple views, driven by a generative relighting model that simulates the e…
SHeaP: Self-Supervised Head Geometry Predictor Learned via 2D Gaussians
Liam Schoneveld, Zhe Chen, Davide Davoli +4
Accurate, real-time 3D reconstruction of human heads from monocular images and videos underlies numerous visual applications. As 3D ground truth data is hard to come by at scale, p…
GAF: Gaussian Avatar Reconstruction from Monocular Videos via Multi-view Diffusion
Jiapeng Tang, Davide Davoli, Tobias Kirschstein +2
We propose a novel approach for reconstructing animatable 3D Gaussian avatars from monocular videos captured by commodity devices like smartphones. Photorealistic 3D head avatar re…
GGHead: Fast and Generalizable 3D Gaussian Heads
Tobias Kirschstein, Simon Giebenhain, Jiapeng Tang +2
Learning 3D head priors from large 2D image collections is an important step towards high-quality 3D-aware human modeling. A core requirement is an efficient architecture that scal…
Surface Normal Estimation with Transformers
Barry Shichen Hu, Siyun Liang, Johannes Paetzold +3
We propose the use of a Transformer to accurately predict normals from point clouds with noise and density variations. Previous learning-based methods utilize PointNet variants to…
Motion2VecSets: 4D Latent Vector Set Diffusion for Non-rigid Shape Reconstruction and Tracking
Wei Cao, Chang Luo, Biao Zhang +2
We introduce Motion2VecSets, a 4D diffusion model for dynamic surface reconstruction from point cloud sequences. While existing state-of-the-art methods have demonstrated success i…
DPHMs: Diffusion Parametric Head Models for Depth-based Tracking
Jiapeng Tang, Angela Dai, Yinyu Nie +3
We introduce Diffusion Parametric Head Models (DPHMs), a generative model that enables robust volumetric head reconstruction and tracking from monocular depth sequences. While rece…
DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesis
Jiapeng Tang, Yinyu Nie, Lev Markhasin +3
We present DiffuScene for indoor 3D scene synthesis based on a novel scene configuration denoising diffusion model. It generates 3D instance properties stored in an unordered objec…