42 citations · 95 across the 20 of their papers we have counts for
21 papers
VisDom: Sparse Novel View Synthesis with Visible Domain Constraint
Mariia Gladkova, Tarun Yenamandra, Edmond Boyer +3
Sparse novel view synthesis (NVS) remains challenging due to the ambiguity of recovering 3D geometry from few input views. While NeRF- and Gaussian Splatting (GS)-based methods per…
ANIM: Accurate Neural Implicit Model for Human Reconstruction from a single RGB-D image
Marco Pesavento, Yuanlu Xu, Nikolaos Sarafianos +7
Recent progress in human shape learning, shows that neural implicit models are effective in generating 3D human surfaces from limited number of views, and even from a single RGB im…
HISR: Hybrid Implicit Surface Representation for Photorealistic 3D Human Reconstruction
Angtian Wang, Yuanlu Xu, Nikolaos Sarafianos +4
Neural reconstruction and rendering strategies have demonstrated state-of-the-art performances due, in part, to their ability to preserve high level shape details. Existing approac…
NSF: Neural Surface Fields for Human Modeling from Monocular Depth
Yuxuan Xue, Bharat Lal Bhatnagar, Riccardo Marin +4
Obtaining personalized 3D animatable avatars from a monocular camera has several real world applications in gaming, virtual try-on, animation, and VR/XR, etc. However, it is very c…
VIVE3D: Viewpoint-Independent Video Editing using 3D-Aware GANs
Anna Frühstück, Nikolaos Sarafianos, Yuanlu Xu +2
We introduce VIVE3D, a novel approach that extends the capabilities of image-based 3D GANs to video editing and is able to represent the input video in an identity-preserving and t…
Multi-View Reconstruction using Signed Ray Distance Functions (SRDF)
Pierre Zins, Yuanlu Xu, Edmond Boyer +2
In this paper, we investigate a new optimization framework for multi-view 3D shape reconstructions. Recent differentiable rendering approaches have provided breakthrough performanc…
Pose-NDF: Modeling Human Pose Manifolds with Neural Distance Fields
Garvita Tiwari, Dimitrije Antic, Jan Eric Lenssen +3
We present Pose-NDF, a continuous model for plausible human poses based on neural distance fields (NDFs). Pose or motion priors are important for generating realistic new poses and…
BodyMap: Learning Full-Body Dense Correspondence Map
Anastasia Ianina, Nikolaos Sarafianos, Yuanlu Xu +2
Dense correspondence between humans carries powerful semantic information that can be utilized to solve fundamental problems for full-body understanding such as in-the-wild surface…
Neural Rendering of Humans in Novel View and Pose from Monocular Video
Tiantian Wang, Nikolaos Sarafianos, Ming-Hsuan Yang +1
We introduce a new method that generates photo-realistic humans under novel views and poses given a monocular video as input. Despite the significant progress recently on this topi…
SPAMs: Structured Implicit Parametric Models
Pablo Palafox, Nikolaos Sarafianos, Tony Tung +1
Parametric 3D models have formed a fundamental role in modeling deformable objects, such as human bodies, faces, and hands; however, the construction of such parametric models requ…
Free-Viewpoint RGB-D Human Performance Capture and Rendering
Phong Nguyen-Ha, Nikolaos Sarafianos, Christoph Lassner +2
Capturing and faithfully rendering photo-realistic humans from novel views is a fundamental problem for AR/VR applications. While prior work has shown impressive performance captur…
Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing
Garvita Tiwari, Nikolaos Sarafianos, Tony Tung +1
We present Neural Generalized Implicit Functions(Neural-GIF), to animate people in clothing as a function of the body pose. Given a sequence of scans of a subject in various poses,…
ARCH++: Animation-Ready Clothed Human Reconstruction Revisited
Tong He, Yuanlu Xu, Shunsuke Saito +2
We present ARCH++, an image-based method to reconstruct 3D avatars with arbitrary clothing styles. Our reconstructed avatars are animation-ready and highly realistic, in both the v…
Data-Driven 3D Reconstruction of Dressed Humans From Sparse Views
Pierre Zins, Yuanlu Xu, Edmond Boyer +2
Recently, data-driven single-view reconstruction methods have shown great progress in modeling 3D dressed humans. However, such methods suffer heavily from depth ambiguities and oc…
Semi-supervised Synthesis of High-Resolution Editable Textures for 3D Humans
Bindita Chaudhuri, Nikolaos Sarafianos, Linda Shapiro +1
We introduce a novel approach to generate diverse high fidelity texture maps for 3D human meshes in a semi-supervised setup. Given a segmentation mask defining the layout of the se…
TexMesh: Reconstructing Detailed Human Texture and Geometry from RGB-D Video
Tiancheng Zhi, Christoph Lassner, Tony Tung +3
We present TexMesh, a novel approach to reconstruct detailed human meshes with high-resolution full-body texture from RGB-D video. TexMesh enables high quality free-viewpoint rende…
SIZER: A Dataset and Model for Parsing 3D Clothing and Learning Size Sensitive 3D Clothing
Garvita Tiwari, Bharat Lal Bhatnagar, Tony Tung +1
While models of 3D clothing learned from real data exist, no method can predict clothing deformation as a function of garment size. In this paper, we introduce SizerNet to predict…
ARCH: Animatable Reconstruction of Clothed Humans
Zeng Huang, Yuanlu Xu, Christoph Lassner +2
In this paper, we propose ARCH (Animatable Reconstruction of Clothed Humans), a novel end-to-end framework for accurate reconstruction of animation-ready 3D clothed humans from a m…
DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-Compare
Yuanlu Xu, Song-Chun Zhu, Tony Tung
We present DenseRaC, a novel end-to-end framework for jointly estimating 3D human pose and body shape from a monocular RGB image. Our two-step framework takes the body pixel-to-sur…
DeepWrinkles: Accurate and Realistic Clothing Modeling
Zorah Laehner, Daniel Cremers, Tony Tung
We present a novel method to generate accurate and realistic clothing deformation from real data capture. Previous methods for realistic cloth modeling mainly rely on intensive com…
Pano2CAD: Room Layout From A Single Panorama Image
Jiu Xu, Bjorn Stenger, Tommi Kerola +1
This paper presents a method of estimating the geometry of a room and the 3D pose of objects from a single 360-degree panorama image. Assuming Manhattan World geometry, we formulat…