5 citations · 5 across the 10 of their papers we have counts for
17 papers
MIRAGE: Metric Inference and Reliability-Aware Gaussian Estimation from Feed-Forward Vision
Xinzhe Wang, Changjian Jiang, Kaiwen Song +8
Feed-forward 3D priors enable high-quality reconstruction from image streams but often lack reliable metric scale and suffer from long-term trajectory drift. In contrast, LiDAR--in…
Real2Gym: Building Gyms from Videos, Bringing Skills to Robots
Kerui Ren, Yingxiang Xu, Kaiwen Song +4
Real-world videos provide rich demonstrations of manipulation, but turning them into reusable robot skills requires visually aligned environments, executable physical interactions,…
InfiniHand: Streaming World-Space Hand Motion Estimation from Egocentric Video
Kerui Ren, Kaiwen Song, Weiguang Zhao +8
World-space hand motion estimation from egocentric video requires recovering 3D articulated hand geometry while tracking camera egomotion. Existing approaches heavily rely on casca…
GeoVerse: World-Consistent Novel View Synthesis in Geometric Latent Space
Kerui Ren, Tao Lu, Linning Xu +5
Novel view synthesis from sparse images must reconcile faithful reconstruction of observed regions with plausible completion of unseen content, while maintaining world consistency…
InternW0-: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data
Xingyu Miao, Zizun Li, Baole Fang +45
World Action Models (WAMs) jointly model visual dynamics and action generation for generalist robot manipulation. A central challenge is to integrate priors from large-scale pretra…
AquaFlow: A Monocular Gaussian Splatting SLAM for Underwater Streaming Reconstruction
Yingxiang Xu, Kerui Ren, Wenqi Guo +4
Recent monocular 3D Gaussian Splatting (3DGS) streaming reconstruction methods have achieved impressive performance by balancing reconstruction quality and efficiency. However, ext…
M^3: Dense Matching Meets Multi-View Foundation Models for Monocular Gaussian Splatting SLAM
Kerui Ren, Guanghao Li, Changjian Jiang +7
Streaming reconstruction from uncalibrated monocular video remains challenging, as it requires both high-precision pose estimation and computationally efficient online refinement i…
SoMA: A Real-to-Sim Neural Simulator for Robotic Soft-body Manipulation
Mu Huang, Hui Wang, Kerui Ren +5
Simulating deformable objects under rich interactions remains a fundamental challenge for real-to-sim robot manipulation, with dynamics jointly driven by environmental effects and…
EAG-PT: Emission-Aware Gaussians and Path Tracing for Diffuse Indoor Scene Reconstruction and Editing
Xijie Yang, Mulin Yu, Changjian Jiang +6
Recent radiance-field-based reconstruction methods, such as NeRF and 3DGS, achieve high visual fidelity for indoor scenes, but often break down under scene editing due to baked ill…
PLANING: A Loosely Coupled Triangle-Gaussian Framework for Streaming 3D Reconstruction
Changjian Jiang, Kerui Ren, Xudong Li +8
Streaming reconstruction from monocular image sequences remains challenging, as existing methods typically favor either high-quality rendering or accurate geometry, but rarely both…
ARTDECO: Towards Efficient and High-Fidelity On-the-Fly 3D Reconstruction with Structured Scene Representation
Guanghao Li, Kerui Ren, Linning Xu +7
On-the-fly 3D reconstruction from monocular image sequences is a long-standing challenge in computer vision, critical for applications such as real-to-sim, AR/VR, and robotics. Exi…
MV-CoLight: Efficient Object Compositing with Consistent Lighting and Shadow Generation
Kerui Ren, Jiayang Bai, Linning Xu +4
Object compositing offers significant promise for augmented reality (AR) and embodied intelligence applications. Existing approaches predominantly focus on single-image scenarios o…
HaloGS: Loose Coupling of Compact Geometry and Gaussian Splats for 3D Scenes
Changjian Jiang, Kerui Ren, Linning Xu +5
High fidelity 3D reconstruction and rendering hinge on capturing precise geometry while preserving photo realistic detail. Most existing methods either fuse these goals into a sing…
AnySplat: Feed-forward 3D Gaussian Splatting from Unconstrained Views
Lihan Jiang, Yucheng Mao, Linning Xu +9
We introduce AnySplat, a feed forward network for novel view synthesis from uncalibrated image collections. In contrast to traditional neural rendering pipelines that demand known…
Novel Demonstration Generation with Gaussian Splatting Enables Robust One-Shot Manipulation
Sizhe Yang, Wenye Yu, Jia Zeng +5
Visuomotor policies learned from teleoperated demonstrations face challenges such as lengthy data collection, high costs, and limited data diversity. Existing approaches address th…
Horizon-GS: Unified 3D Gaussian Splatting for Large-Scale Aerial-to-Ground Scenes
Lihan Jiang, Kerui Ren, Mulin Yu +6
Seamless integration of both aerial and street view images remains a significant challenge in neural scene reconstruction and rendering. Existing methods predominantly focus on sin…
Octree-GS: Towards Consistent Real-time Rendering with LOD-Structured 3D Gaussians
Kerui Ren, Lihan Jiang, Tao Lu +4
The recent 3D Gaussian splatting (3D-GS) has shown remarkable rendering fidelity and efficiency compared to NeRF-based neural scene representations. While demonstrating the potenti…