41 citations · 49 across the 18 of their papers we have counts for
18 papers
VoxScene: Anchor-Conditioned Voxel Diffusion for Indoor Scene Arrangement
Haotian Mao, Yuhan Huang, Jiatao Lin +8
We present VoxScene, a novel anchor-conditioned voxel diffusion framework tailored for 3D scene synthesis. Current data-driven layout generation techniques typically rely on boundi…
Learning-guided Kansa collocation for forward and inverse PDEs beyond linearity
Zheyuan Hu, Weitao Chen, Cengiz Öztireli +2
Partial Differential Equations are precise in modelling the physical, biological and graphical phenomena. However, the numerical methods suffer from the curse of dimensionality, hi…
PoseCraft: Tokenized 3D Body Landmark and Camera Conditioning for Photorealistic Human Image Synthesis
Zhilin Guo, Jing Yang, Kyle Fogarty +9
Digitizing humans and synthesizing photorealistic avatars with explicit 3D pose and camera controls are central to VR, telepresence, and entertainment. Existing skinning-based work…
Quartet of Diffusions: Structure-Aware Point Cloud Generation through Part and Symmetry Guidance
Chenliang Zhou, Fangcheng Zhong, Weihao Xia +3
We introduce the Quartet of Diffusions, a structure-aware point cloud generation framework that explicitly models part composition and symmetry. Unlike prior methods that treat sha…
LiteReality: Graphics-Ready 3D Scene Reconstruction from RGB-D Scans
Zhening Huang, Xiaoyang Wu, Fangcheng Zhong +3
We propose LiteReality, a novel pipeline that converts RGB-D scans of indoor environments into compact, realistic, and interactive 3D virtual replicas. LiteReality not only reconst…
Physically Based Neural Bidirectional Reflectance Distribution Function
Chenliang Zhou, Alejandro Sztrajman, Gilles Rainer +6
We introduce the physically based neural bidirectional reflectance distribution function (PBNBRDF), a novel, continuous representation for material appearance based on neural field…
SYM3D: Learning Symmetric Triplanes for Better 3D-Awareness of GANs
Jing Yang, Kyle Fogarty, Fangcheng Zhong +1
Despite the growing success of 3D-aware GANs, which can be trained on 2D images to generate high-quality 3D assets, they still rely on multi-view images with camera annotations to…
Gaussian Head & Shoulders: High Fidelity Neural Upper Body Avatars with Anchor Gaussian Guided Texture Warping
Tianhao Wu, Jing Yang, Zhilin Guo +3
By equipping the most recent 3D Gaussian Splatting representation with head 3D morphable models (3DMM), existing methods manage to create head avatars with high fidelity. However,…
Differentiable Visual Computing for Inverse Problems and Machine Learning
Andrew Spielberg, Fangcheng Zhong, Konstantinos Rematas +4
Originally designed for applications in computer graphics, visual computing (VC) methods synthesize information about physical and virtual worlds, using prescribed algorithms optim…
Hypernetworks for Generalizable BRDF Representation
Fazilet Gokbudak, Alejandro Sztrajman, Chenliang Zhou +3
In this paper, we introduce a technique to estimate measured BRDFs from a sparse set of samples. Our approach offers accurate BRDF reconstructions that are generalizable to new mat…
FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation
Chenliang Zhou, Fangcheng Zhong, Param Hanji +5
We propose FrePolad: frequency-rectified point latent diffusion, a point cloud generation pipeline integrating a variational autoencoder (VAE) with a denoising diffusion probabilis…
ARF-Plus: Controlling Perceptual Factors in Artistic Radiance Fields for 3D Scene Stylization
Wenzhao Li, Tianhao Wu, Fangcheng Zhong +1
The radiance fields style transfer is an emerging field that has recently gained popularity as a means of 3D scene stylization, thanks to the outstanding performance of neural radi…
Neural Fields with Hard Constraints of Arbitrary Differential Order
Fangcheng Zhong, Kyle Fogarty, Param Hanji +6
While deep learning techniques have become extremely popular for solving a broad range of optimization problems, methods to enforce hard constraints during optimization, particular…
Surf: Implicit Surface Reconstruction for Semi-Transparent and Thin Objects with Decoupled Geometry and Opacity
Tianhao Wu, Hanxue Liang, Fangcheng Zhong +4
Implicit surface representations such as the signed distance function (SDF) have emerged as a promising approach for image-based surface reconstruction. However, existing optimizat…
CLIP-PAE: Projection-Augmentation Embedding to Extract Relevant Features for a Disentangled, Interpretable, and Controllable Text-Guided Face Manipulation
Chenliang Zhou, Fangcheng Zhong, Cengiz Oztireli
Recently introduced Contrastive Language-Image Pre-Training (CLIP) bridges images and text by embedding them into a joint latent space. This opens the door to ample literature that…
DNeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Video
Tianhao Wu, Fangcheng Zhong, Andrea Tagliasacchi +2
Given a monocular video, segmenting and decoupling dynamic objects while recovering the static environment is a widely studied problem in machine intelligence. Existing solutions u…
Kubric: A scalable dataset generator
Klaus Greff, Francois Belletti, Lucas Beyer +32
Data is the driving force of machine learning, with the amount and quality of training data often being more important for the performance of a system than architecture and trainin…
Noise-Aware Merging of High Dynamic Range Image Stacks without Camera Calibration
Param Hanji, Fangcheng Zhong, Rafal K. Mantiuk
A near-optimal reconstruction of the radiance of a High Dynamic Range scene from an exposure stack can be obtained by modeling the camera noise distribution. The latent radiance is…