1 citations · 2 across the 7 of their papers we have counts for
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StdGEN++: A Comprehensive System for Semantic-Decomposed 3D Character Generation
Yuze He, Yanning Zhou, Wang Zhao +4
We present StdGEN++, a novel and comprehensive system for generating high-fidelity, semantically decomposed 3D characters from diverse inputs. Existing 3D generative methods often…
AlphaTablets: A Generic Plane Representation for 3D Planar Reconstruction from Monocular Videos
Yuze He, Wang Zhao, Shaohui Liu +4
We introduce AlphaTablets, a novel and generic representation of 3D planes that features continuous 3D surface and precise boundary delineation. By representing 3D planes as rectan…
StdGEN: Semantic-Decomposed 3D Character Generation from Single Images
Yuze He, Yanning Zhou, Wang Zhao +5
We present StdGEN, an innovative pipeline for generating semantically decomposed high-quality 3D characters from single images, enabling broad applications in virtual reality, gami…
PVP-Recon: Progressive View Planning via Warping Consistency for Sparse-View Surface Reconstruction
Sheng Ye, Yuze He, Matthieu Lin +8
Neural implicit representations have revolutionized dense multi-view surface reconstruction, yet their performance significantly diminishes with sparse input views. A few pioneerin…
Text-Image Conditioned Diffusion for Consistent Text-to-3D Generation
Yuze He, Yushi Bai, Matthieu Lin +5
By lifting the pre-trained 2D diffusion models into Neural Radiance Fields (NeRFs), text-to-3D generation methods have made great progress. Many state-of-the-art approaches usually…
TBench: Benchmarking Current Progress in Text-to-3D Generation
Yuze He, Yushi Bai, Matthieu Lin +6
Recent methods in text-to-3D leverage powerful pretrained diffusion models to optimize NeRF. Notably, these methods are able to produce high-quality 3D scenes without training on 3…