4 citations · 7 across the 12 of their papers we have counts for
13 papers
Dynamic Visual SLAM using a General 3D Prior
Xingguang Zhong, Liren Jin, Marija Popović +2
Reliable incremental estimation of camera poses and 3D reconstruction is key to enable various applications including robotics, interactive visualization, and augmented reality. Ho…
Globally Consistent RGB-D SLAM with 2D Gaussian Splatting
Xingguang Zhong, Yue Pan, Liren Jin +3
Recently, 3D Gaussian splatting-based RGB-D SLAM displays remarkable performance of high-fidelity 3D reconstruction. However, the lack of depth rendering consistency and efficient…
DM-OSVP++: One-Shot View Planning Using 3D Diffusion Models for Active RGB-Based Object Reconstruction
Sicong Pan, Liren Jin, Xuying Huang +3
Active object reconstruction is crucial for many robotic applications. A key aspect in these scenarios is generating object-specific view configurations to obtain informative measu…
PINGS: Gaussian Splatting Meets Distance Fields within a Point-Based Implicit Neural Map
Yue Pan, Xingguang Zhong, Liren Jin +4
Robots benefit from high-fidelity reconstructions of their environment, which should be geometrically accurate and photorealistic to support downstream tasks. While this can be ach…
ActiveGS: Active Scene Reconstruction Using Gaussian Splatting
Liren Jin, Xingguang Zhong, Yue Pan +3
Robotics applications often rely on scene reconstructions to enable downstream tasks. In this work, we tackle the challenge of actively building an accurate map of an unknown scene…
STAIR: Semantic-Targeted Active Implicit Reconstruction
Liren Jin, Haofei Kuang, Yue Pan +2
Many autonomous robotic applications require object-level understanding when deployed. Actively reconstructing objects of interest, i.e. objects with specific semantic meanings, is…
Exploiting Priors from 3D Diffusion Models for RGB-Based One-Shot View Planning
Sicong Pan, Liren Jin, Xuying Huang +3
Object reconstruction is relevant for many autonomous robotic tasks that require interaction with the environment. A key challenge in such scenarios is planning view configurations…
Active Implicit Reconstruction Using One-Shot View Planning
Hao Hu, Sicong Pan, Liren Jin +2
Active object reconstruction using autonomous robots is gaining great interest. A primary goal in this task is to maximize the information of the object to be reconstructed, given…
How Many Views Are Needed to Reconstruct an Unknown Object Using NeRF?
Sicong Pan, Liren Jin, Hao Hu +2
Neural Radiance Fields (NeRFs) are gaining significant interest for online active object reconstruction due to their exceptional memory efficiency and requirement for only posed RG…
NeU-NBV: Next Best View Planning Using Uncertainty Estimation in Image-Based Neural Rendering
Liren Jin, Xieyuanli Chen, Julius Rückin +1
Autonomous robotic tasks require actively perceiving the environment to achieve application-specific goals. In this paper, we address the problem of positioning an RGB camera to co…
Informative Path Planning for Active Learning in Aerial Semantic Mapping
Julius Rückin, Liren Jin, Federico Magistri +2
Semantic segmentation of aerial imagery is an important tool for mapping and earth observation. However, supervised deep learning models for segmentation rely on large amounts of h…
Adaptive-Resolution Field Mapping Using Gaussian Process Fusion with Integral Kernels
Liren Jin, Julius Rückin, Stefan H. Kiss +2
Unmanned aerial vehicles are rapidly gaining popularity in a variety of environmental monitoring tasks. A key requirement for their autonomous operation is the ability to perform e…
Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing
Julius Rückin, Liren Jin, Marija Popović
Aerial robots are increasingly being utilized for environmental monitoring and exploration. However, a key challenge is efficiently planning paths to maximize the information value…