4 papers · 1 filter
D-Aug: Enhancing Data Augmentation for Dynamic LiDAR Scenes
Jiaxing Zhao, Peng Zheng, Rui Ma
Creating large LiDAR datasets with pixel-level labeling poses significant challenges. While numerous data augmentation methods have been developed to reduce the reliance on manual…
SemanticHuman-HD: High-Resolution Semantic Disentangled 3D Human Generation
Peng Zheng, Tao Liu, Zili Yi +1
With the development of neural radiance fields and generative models, numerous methods have been proposed for learning 3D human generation from 2D images. These methods allow contr…
TaylorGrid: Towards Fast and High-Quality Implicit Field Learning via Direct Taylor-based Grid Optimization
Renyi Mao, Qingshan Xu, Peng Zheng +3
Coordinate-based neural implicit representation or implicit fields have been widely studied for 3D geometry representation or novel view synthesis. Recently, a series of efforts ha…
3D-SSGAN: Lifting 2D Semantics for 3D-Aware Compositional Portrait Synthesis
Ruiqi Liu, Peng Zheng, Ye Wang +1
Existing 3D-aware portrait synthesis methods can generate impressive high-quality images while preserving strong 3D consistency. However, most of them cannot support the fine-grain…