157 citations · 159 across the 8 of their papers we have counts for
8 papers
X-Tokenizer: A Multimodal Action Tokenizer for Vision-Language-Action Pretraining
Miracle Kang, Lights Shi, Lucy Liang +10
Modern Vision-Language-Action (VLA) models must bridge pretrained vision-language reasoning and precise continuous robot control. Existing action tokenizers discretize actions prim…
XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications
Shangjin Zhai, Nan Wang, Xiaomeng Wang +4
This paper presents a novel approach to Visual Inertial Odometry (VIO), focusing on the initialization and feature matching modules. Existing methods for initialization often suffe…
StarGen: A Spatiotemporal Autoregression Framework with Video Diffusion Model for Scalable and Controllable Scene Generation
Shangjin Zhai, Zhichao Ye, Jialin Liu +10
Recent advances in large reconstruction and generative models have significantly improved scene reconstruction and novel view generation. However, due to compute limitations, each…
CoSurfGS:Collaborative 3D Surface Gaussian Splatting with Distributed Learning for Large Scene Reconstruction
Yuanyuan Gao, Yalun Dai, Hao Li +7
3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or…
GigaGS: Scaling up Planar-Based 3D Gaussians for Large Scene Surface Reconstruction
Junyi Chen, Weicai Ye, Yifan Wang +6
3D Gaussian Splatting (3DGS) has shown promising performance in novel view synthesis. Previous methods adapt it to obtaining surfaces of either individual 3D objects or within limi…
PGSR: Planar-based Gaussian Splatting for Efficient and High-Fidelity Surface Reconstruction
Danpeng Chen, Hai Li, Weicai Ye +7
Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstru…
Depth Completion with Multiple Balanced Bases and Confidence for Dense Monocular SLAM
Weijian Xie, Guanyi Chu, Quanhao Qian +7
Dense SLAM based on monocular cameras does indeed have immense application value in the field of AR/VR, especially when it is performed on a mobile device. In this paper, we propos…
VIP-SLAM: An Efficient Tightly-Coupled RGB-D Visual Inertial Planar SLAM
Danpeng Chen, Shuai Wang, Weijian Xie +4
In this paper, we propose a tightly-coupled SLAM system fused with RGB, Depth, IMU and structured plane information. Traditional sparse points based SLAM systems always maintain a…