2 citations · 2 across the 14 of their papers we have counts for
16 papers
GS-PI: An Optimization-Decoupled Appearance Decomposition Approach for Generating PBR Gaussian Assets
Jieting Xu, Rengan Xie, Zijian Huang +3
Gaussian Splatting (GS) excels at novel-view synthesis but encodes baked-in radiance, tightly entangling illumination with geometry and preventing seamless integration into physica…
ESG: Generating Physically Consistent Dynamic 3D Scenes from Text Descriptions
Xintong Fang, Zhiyuan Fang, Rengan Xie +6
Recent progress in image and 3D scene generation has enabled increasingly realistic static environments, yet most methods remain confined to such static configurations. Generating…
ES3D: Embedding Semantics into 3D Space for Component-Aware Editing
Xuancheng Jin, Rengan Xie, Jiayuan Lu +5
Existing 3D editing methods have made notable progress in controllability, yet they remain limited in several important ways. Most approaches rely on text-driven editing, which str…
HIVE-3D: Hierarchical Voxel Enhancement for High-Quality 3D Scene Generation
Bin Zang, Wenting Zheng, Xiaoliang Luo +8
Recently, a line of works can generate impressive 3D objects from a single image, but they are limited by restricted representation resolution, making them unsuitable for 3D scene…
Texture++: Elevating 3D Asset Texture Resolution with a Region-Aware Diffusion Model
Shuaiwei Wang, Shi Li, Jieting Xu +4
Numerous 3D assets are discarded due to low texture resolution, while current super-resolution models ignore texture maps and focus on natural images. An efficient and generalizabl…
LiDAR-GS++:Improving LiDAR Gaussian Reconstruction via Diffusion Priors
Qifeng Chen, Jiarun Liu, Rengan Xie +5
Recent GS-based rendering has made significant progress for LiDAR, surpassing Neural Radiance Fields (NeRF) in both quality and speed. However, these methods exhibit artifacts in e…
Leveraging Pretrained Diffusion Models for Zero-Shot Part Assembly
Ruiyuan Zhang, Qi Wang, Jiaxiang Liu +3
3D part assembly aims to understand part relationships and predict their 6-DoF poses to construct realistic 3D shapes, addressing the growing demand for autonomous assembly, which…
SGW-based Multi-Task Learning in Vision Tasks
Ruiyuan Zhang, Yuyao Chen, Yuchi Huo +4
Multi-task-learning(MTL) is a multi-target optimization task. Neural networks try to realize each target using a shared interpretative space within MTL. However, as the scale of da…
LiDAR-GS:Real-time LiDAR Re-Simulation using Gaussian Splatting
Qifeng Chen, Sheng Yang, Sicong Du +4
We present LiDAR-GS, a Gaussian Splatting (GS) method for real-time, high-fidelity re-simulation of LiDAR scans in public urban road scenes. Recent GS methods proposed for cameras…
AdaptiveFusion: Adaptive Multi-Modal Multi-View Fusion for 3D Human Body Reconstruction
Anjun Chen, Xiangyu Wang, Zhi Xu +5
Recent advancements in sensor technology and deep learning have led to significant progress in 3D human body reconstruction. However, most existing approaches rely on data from a s…
Inverse Rendering using Multi-Bounce Path Tracing and Reservoir Sampling
Yuxin Dai, Qi Wang, Jingsen Zhu +4
We present MIRReS, a novel two-stage inverse rendering framework that jointly reconstructs and optimizes the explicit geometry, material, and lighting from multi-view images. Unlik…
HR Human: Modeling Human Avatars with Triangular Mesh and High-Resolution Textures from Videos
Qifeng Chen, Rengan Xie, Kai Huang +4
Recently, implicit neural representation has been widely used to generate animatable human avatars. However, the materials and geometry of those representations are coupled in the…
LDM: Large Tensorial SDF Model for Textured Mesh Generation
Rengan Xie, Wenting Zheng, Kai Huang +5
Previous efforts have managed to generate production-ready 3D assets from text or images. However, these methods primarily employ NeRF or 3D Gaussian representations, which are not…
CT-NeRF: Incremental Optimizing Neural Radiance Field and Poses with Complex Trajectory
Yunlong Ran, Yanxu Li, Qi Ye +4
Neural radiance field (NeRF) has achieved impressive results in high-quality 3D scene reconstruction. However, NeRF heavily relies on precise camera poses. While recent works like…
2L3: Lifting Imperfect Generated 2D Images into Accurate 3D
Yizheng Chen, Rengan Xie, Qi Ye +5
Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV…
In-Hand 3D Object Reconstruction from a Monocular RGB Video
Shijian Jiang, Qi Ye, Rengan Xie +4
Our work aims to reconstruct a 3D object that is held and rotated by a hand in front of a static RGB camera. Previous methods that use implicit neural representations to recover th…