14 citations · 29 across the 10 of their papers we have counts for
11 papers
Elevator-VIGS: Separating Elevator Motion from Robot Motion in Visual-Inertial Gaussian Splatting SLAM
Rui Zhou, Zihan Zhu, Wei Zhang +3
We present Elevator-VIGS, a visual-inertial 3D Gaussian Splatting SLAM system that keeps tracking and mapping through elevator rides. Inside a moving elevator, the two sensors are…
Intrinsic and Triangulation-Agnostic Attention: A Simple and Powerful Approach for Learning on Meshes
Ashwath Shetty, Zihan Zhu, Soeren Pirk +1
This work proposes an adaptation of the attention mechanism for triangle meshes. The core observation is that endowing the attention mechanism with critical properties for learning…
WildPose: A Unified Framework for Robust Pose Estimation in the Wild
Jianhao Zheng, Liyuan Zhu, Zihan Zhu +1
Estimating camera pose in dynamic environments is a critical challenge, as most visual SLAM and SfM methods assume static scenes. While recent dynamic-aware methods exist, they are…
DROID-SLAM in the Wild
Moyang Li, Zihan Zhu, Marc Pollefeys +1
We present a robust, real-time RGB SLAM system that handles dynamic environments by leveraging differentiable Uncertainty-aware Bundle Adjustment. Traditional SLAM methods typicall…
VIGS-SLAM: Visual Inertial Gaussian Splatting SLAM
Zihan Zhu, Wei Zhang, Moyang Li +3
We present VIGS-SLAM, a visual-inertial 3D Gaussian Splatting SLAM system that achieves robust real-time tracking and high-fidelity reconstruction. Although recent 3DGS-based SLAM…
MCGS-SLAM: A Multi-Camera SLAM Framework Using Gaussian Splatting for High-Fidelity Mapping
Zhihao Cao, Hanyu Wu, Li Wa Tang +5
Recent progress in dense SLAM has primarily targeted monocular setups, often at the expense of robustness and geometric coverage. We present MCGS-SLAM, the first purely RGB-based m…
WildGS-SLAM: Monocular Gaussian Splatting SLAM in Dynamic Environments
Jianhao Zheng, Zihan Zhu, Valentin Bieri +3
We present WildGS-SLAM, a robust and efficient monocular RGB SLAM system designed to handle dynamic environments by leveraging uncertainty-aware geometric mapping. Unlike tradition…
NeRF On-the-go: Exploiting Uncertainty for Distractor-free NeRFs in the Wild
Weining Ren, Zihan Zhu, Boyang Sun +3
Neural Radiance Fields (NeRFs) have shown remarkable success in synthesizing photorealistic views from multi-view images of static scenes, but face challenges in dynamic, real-worl…
NICER-SLAM: Neural Implicit Scene Encoding for RGB SLAM
Zihan Zhu, Songyou Peng, Viktor Larsson +4
Neural implicit representations have recently become popular in simultaneous localization and mapping (SLAM), especially in dense visual SLAM. However, previous works in this direc…
Hybrid Mesh-neural Representation for 3D Transparent Object Reconstruction
Jiamin Xu, Zihan Zhu, Hujun Bao +1
We propose a novel method to reconstruct the 3D shapes of transparent objects using hand-held captured images under natural light conditions. It combines the advantage of explicit…
NICE-SLAM: Neural Implicit Scalable Encoding for SLAM
Zihan Zhu, Songyou Peng, Viktor Larsson +5
Neural implicit representations have recently shown encouraging results in various domains, including promising progress in simultaneous localization and mapping (SLAM). Neverthele…