12 citations · 13 across the 20 of their papers we have counts for
21 papers
Hierarchical Flow Matching for 3D Point Cloud Generation
Linhao Wang, Qichang Zhang, Ye Su +1
Generating high-quality 3D point clouds requires capturing both global shape topology and local geometric details. Existing flow-based methods rely on continuous normalizing flows…
Robust and Efficient Monocular 3D Gaussian SLAM for Kilometer-Scale Outdoor Scenes
Sicheng Yu, Dongxu Shen, Beizhen Zhao +2
Scaling monocular 3D Gaussian Splatting (3DGS) SLAM to kilometer-level outdoor environments poses two tightly coupled challenges: fragile long-term pose tracking and excessive memo…
HorizonStream: Long-Horizon Attention for Streaming 3D Reconstruction
Chong Cheng, Peilin Tao, Nanjie Yao +9
Online 3D reconstruction requires estimating camera pose and scene geometry under strict causal and bounded-memory constraints. Existing methods often suffer from drift, jitter, or…
Generator-Refiner-Examiner: A Tri-Module Data Augmentation Framework for 3D Human Avatar Learning from Monocular Videos
Gangjian Zhang, Jian Shu, Sicheng Yu +3
This paper addresses the challenge of reconstructing photorealistic and animatable 3D human avatars from monocular videos. While existing methods rely on combining per-subject opti…
MMGS: 10 Compressed 3DGS through Optimal Transport Aggregation based on Multi-view Ranking
Beizhen Zhao, Sicheng Yu, Ziran Yin +2
While 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction, it suffers from significant overhead due to massive redundant primitives. Existing compression methods typi…
3D Skew Gaussian Splatting with Any Camera Trajectory Visualization Engine
Beizhen Zhao, Yifan Zhou, Gaochao Song +2
While 3D Gaussian Splatting (3DGS) has revolutionized real-time photorealistic view synthesis, its fundamental reliance on symmetric Gaussian distributions introduces visual artifa…
LongStream: Long-Sequence Streaming Autoregressive Visual Geometry
Chong Cheng, Xianda Chen, Tao Xie +5
Long-sequence streaming 3D reconstruction remains a significant open challenge. Existing autoregressive models often fail when processing long sequences because they anchor poses t…
Pseudo-View Enhancement via Confidence Fusion for Unposed Sparse-View Reconstruction
Beizhen Zhao, Sicheng Yu, Guanzhi Ding +2
3D scene reconstruction under unposed sparse viewpoints is a highly challenging yet practically important problem, especially in outdoor scenes due to complex lighting and scale va…
VGGT4D: Mining Motion Cues in Visual Geometry Transformers for 4D Scene Reconstruction
Yu Hu, Chong Cheng, Sicheng Yu +2
Reconstructing dynamic 4D scenes is challenging, as it requires robust disentanglement of dynamic objects from the static background. While 3D foundation models like VGGT provide a…
Laplacian Analysis Meets Dynamics Modelling: Gaussian Splatting for 4D Reconstruction
Yifan Zhou, Beizhen Zhao, Pengcheng Wu +1
While 3D Gaussian Splatting (3DGS) excels in static scene modeling, its extension to dynamic scenes introduces significant challenges. Existing dynamic 3DGS methods suffer from eit…
Perceive-Sample-Compress: Towards Real-Time 3D Gaussian Splatting
Zijian Wang, Beizhen Zhao, Hao Wang
Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated remarkable capabilities in real-time and photorealistic novel view synthesis. However, traditional 3DGS representa…
Unposed 3DGS Reconstruction with Probabilistic Procrustes Mapping
Chong Cheng, Zijian Wang, Sicheng Yu +3
3D Gaussian Splatting (3DGS) has emerged as a core technique for 3D representation. Its effectiveness largely depends on precise camera poses and accurate point cloud initializatio…
Outdoor Monocular SLAM with Global Scale-Consistent 3D Gaussian Pointmaps
Chong Cheng, Sicheng Yu, Zijian Wang +2
3D Gaussian Splatting (3DGS) has become a popular solution in SLAM due to its high-fidelity and real-time novel view synthesis performance. However, some previous 3DGS SLAM methods…
Wavelet-GS: 3D Gaussian Splatting with Wavelet Decomposition
Beizhen Zhao, Yifan Zhou, Sicheng Yu +2
3D Gaussian Splatting (3DGS) has revolutionized 3D scene reconstruction, which effectively balances rendering quality, efficiency, and speed. However, existing 3DGS approaches usua…
RegGS: Unposed Sparse Views Gaussian Splatting with 3DGS Registration
Chong Cheng, Yu Hu, Sicheng Yu +3
3D Gaussian Splatting (3DGS) has demonstrated its potential in reconstructing scenes from unposed images. However, optimization-based 3DGS methods struggle with sparse views due to…
EG-Gaussian: Epipolar Geometry and Graph Network Enhanced 3D Gaussian Splatting
Beizhen Zhao, Yifan Zhou, Zijian Wang +1
In this paper, we explore an open research problem concerning the reconstruction of 3D scenes from images. Recent methods have adopt 3D Gaussian Splatting (3DGS) to produce 3D scen…
EAGLE: Contextual Point Cloud Generation via Adaptive Continuous Normalizing Flow with Self-Attention
Linhao Wang, Qichang Zhang, Yifan Yang +2
As 3D point clouds become the prevailing shape representation in computer vision, generating high-quality point clouds remains a challenging problem. Flow-based models have shown s…
Graph-Guided Scene Reconstruction from Images with 3D Gaussian Splatting
Chong Cheng, Gaochao Song, Yiyang Yao +3
This paper investigates an open research challenge of reconstructing high-quality, large 3D open scenes from images. It is observed existing methods have various limitations, such…
RGB-Only Gaussian Splatting SLAM for Unbounded Outdoor Scenes
Sicheng Yu, Chong Cheng, Yifan Zhou +2
3D Gaussian Splatting (3DGS) has become a popular solution in SLAM, as it can produce high-fidelity novel views. However, previous GS-based methods primarily target indoor scenes a…
GVKF: Gaussian Voxel Kernel Functions for Highly Efficient Surface Reconstruction in Open Scenes
Gaochao Song, Chong Cheng, Hao Wang
In this paper we present a novel method for efficient and effective 3D surface reconstruction in open scenes. Existing Neural Radiance Fields (NeRF) based works typically require e…
DOCTR: Disentangled Object-Centric Transformer for Point Scene Understanding
Xiaoxuan Yu, Hao Wang, Weiming Li +3
Point scene understanding is a challenging task to process real-world scene point cloud, which aims at segmenting each object, estimating its pose, and reconstructing its mesh simu…