7 citations · 12 across the 8 of their papers we have counts for
6 papers · 1 filter
CEI-3D: Collaborative Explicit-Implicit 3D Reconstruction for Realistic and Fine-Grained Object Editing
Yue Shi, Rui Shi, Yuxuan Xiong +2
Existing 3D editing methods often produce unrealistic and unrefined results due to the deeply integrated nature of their reconstruction networks. To address the challenge, this pap…
InstantSticker: Realistic Decal Blending via Disentangled Object Reconstruction
Yi Zhang, Xiaoyang Huang, Yishun Dou +5
We present InstantSticker, a disentangled reconstruction pipeline based on Image-Based Lighting (IBL), which focuses on highly realistic decal blending, simulates stickers attached…
DualNeRF: Text-Driven 3D Scene Editing via Dual-Field Representation
Yuxuan Xiong, Yue Shi, Yishun Dou +1
Recently, denoising diffusion models have achieved promising results in 2D image generation and editing. Instruct-NeRF2NeRF (IN2N) introduces the success of diffusion into 3D scene…
SelfTalk: A Self-Supervised Commutative Training Diagram to Comprehend 3D Talking Faces
Ziqiao Peng, Yihao Luo, Yue Shi +5
Speech-driven 3D face animation technique, extending its applications to various multimedia fields. Previous research has generated promising realistic lip movements and facial exp…
USR: Unsupervised Separated 3D Garment and Human Reconstruction via Geometry and Semantic Consistency
Yue Shi, Yuxuan Xiong, Jingyi Chai +2
Dressed people reconstruction from images is a popular task with promising applications in the creative media and game industry. However, most existing methods reconstruct the huma…
DARF: Depth-Aware Generalizable Neural Radiance Field
Yue Shi, Dingyi Rong, Chang Chen +3
Neural Radiance Field (NeRF) has revolutionized novel-view rendering tasks and achieved impressive results. However, the inefficient sampling and per-scene optimization hinder its…