526 citations · 1.4k across the 51 of their papers we have counts for
9 papers · 1 filter
FaceTalk: Audio-Driven Motion Diffusion for Neural Parametric Head Models
Shivangi Aneja, Justus Thies, Angela Dai +1
We introduce FaceTalk, a novel generative approach designed for synthesizing high-fidelity 3D motion sequences of talking human heads from input audio signal. To capture the expres…
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…
MeshGPT: Generating Triangle Meshes with Decoder-Only Transformers
Yawar Siddiqui, Antonio Alliegro, Alexey Artemov +5
We introduce MeshGPT, a new approach for generating triangle meshes that reflects the compactness typical of artist-created meshes, in contrast to dense triangle meshes extracted b…
ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenes
Chandan Yeshwanth, Yueh-Cheng Liu, Matthias Nießner +1
We present ScanNet++, a large-scale dataset that couples together capture of high-quality and commodity-level geometry and color of indoor scenes. Each scene is captured with a hig…
Mesh2Tex: Generating Mesh Textures from Image Queries
Alexey Bokhovkin, Shubham Tulsiani, Angela Dai
Remarkable advances have been achieved recently in learning neural representations that characterize object geometry, while generating textured objects suitable for downstream appl…
HyperDiffusion: Generating Implicit Neural Fields with Weight-Space Diffusion
Ziya Erkoç, Fangchang Ma, Qi Shan +2
Implicit neural fields, typically encoded by a multilayer perceptron (MLP) that maps from coordinates (e.g., xyz) to signals (e.g., signed distances), have shown remarkable promise…
UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes
David Rozenberszki, Or Litany, Angela Dai
3D instance segmentation is fundamental to geometric understanding of the world around us. Existing methods for instance segmentation of 3D scenes rely on supervision from expensiv…
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…
Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors
Ji Hou, Xiaoliang Dai, Zijian He +2
Current popular backbones in computer vision, such as Vision Transformers (ViT) and ResNets are trained to perceive the world from 2D images. However, to more effectively understan…