12 citations · 36 across the 17 of their papers we have counts for
8 papers · 1 filter
FINER: Flexible spectral-bias tuning in Implicit NEural Representation by Variable-periodic Activation Functions
Zhen Liu, Hao Zhu, Qi Zhang +5
Implicit Neural Representation (INR), which utilizes a neural network to map coordinate inputs to corresponding attributes, is causing a revolution in the field of signal processin…
RHINO: Regularizing the Hash-based Implicit Neural Representation
Hao Zhu, Fengyi Liu, Qi Zhang +2
The use of Implicit Neural Representation (INR) through a hash-table has demonstrated impressive effectiveness and efficiency in characterizing intricate signals. However, current…
Anti-Aliased Neural Implicit Surfaces with Encoding Level of Detail
Yiyu Zhuang, Qi Zhang, Ying Feng +6
We present LoD-NeuS, an efficient neural representation for high-frequency geometry detail recovery and anti-aliased novel view rendering. Drawing inspiration from voxel-based repr…
AvatarBooth: High-Quality and Customizable 3D Human Avatar Generation
Yifei Zeng, Yuanxun Lu, Xinya Ji +3
We introduce AvatarBooth, a novel method for generating high-quality 3D avatars using text prompts or specific images. Unlike previous approaches that can only synthesize avatars b…
High-Fidelity 3D Face Generation from Natural Language Descriptions
Menghua Wu, Hao Zhu, Linjia Huang +3
Synthesizing high-quality 3D face models from natural language descriptions is very valuable for many applications, including avatar creation, virtual reality, and telepresence. Ho…
NeAI: A Pre-convoluted Representation for Plug-and-Play Neural Ambient Illumination
Yiyu Zhuang, Qi Zhang, Xuan Wang +5
Recent advances in implicit neural representation have demonstrated the ability to recover detailed geometry and material from multi-view images. However, the use of simplified lig…
Disorder-invariant Implicit Neural Representation
Hao Zhu, Shaowen Xie, Zhen Liu +6
Implicit neural representation (INR) characterizes the attributes of a signal as a function of corresponding coordinates which emerges as a sharp weapon for solving inverse problem…
RAFaRe: Learning Robust and Accurate Non-parametric 3D Face Reconstruction from Pseudo 2D&3D Pairs
Longwei Guo, Hao Zhu, Yuanxun Lu +2
We propose a robust and accurate non-parametric method for single-view 3D face reconstruction (SVFR). While tremendous efforts have been devoted to parametric SVFR, a visible gap s…