231 citations · 303 across the 16 of their papers we have counts for
11 papers · 1 filter
D-Prism: Differentiable Primitives for Structured Dynamic Modeling
Xingyuan Yu, Yijin Li, Chong Zeng +3
Capturing both geometry and rigid motion for structured dynamic objects, like multi-part assemblies or jointed mechanisms, remains a key challenge. Existing dynamic methods, such a…
Thermal odometry and dense mapping using learned odometry and Gaussian splatting
Tianhao Zhou, Yujia Chen, Zhihao Zhan +2
Thermal infrared sensors, with wavelengths longer than smoke particles, can capture imagery independent of darkness, dust, and smoke. This robustness has made them increasingly val…
VIPeR: Visual Incremental Place Recognition with Adaptive Mining and Continual Learning
Yuhang Ming, Minyang Xu, Xingrui Yang +5
Visual place recognition (VPR) is an essential component of many autonomous and augmented/virtual reality systems. It enables the systems to robustly localize themselves in large-s…
Vox-Fusion++: Voxel-based Neural Implicit Dense Tracking and Mapping with Multi-maps
Hongjia Zhai, Hai Li, Xingrui Yang +4
In this paper, we introduce Vox-Fusion++, a multi-maps-based robust dense tracking and mapping system that seamlessly fuses neural implicit representations with traditional volumet…
AEGIS-Net: Attention-guided Multi-Level Feature Aggregation for Indoor Place Recognition
Yuhang Ming, Jian Ma, Xingrui Yang +3
We present AEGIS-Net, a novel indoor place recognition model that takes in RGB point clouds and generates global place descriptors by aggregating lower-level color, geometry featur…
Vox-Fusion: Dense Tracking and Mapping with Voxel-based Neural Implicit Representation
Xingrui Yang, Hai Li, Hongjia Zhai +3
In this work, we present a dense tracking and mapping system named Vox-Fusion, which seamlessly fuses neural implicit representations with traditional volumetric fusion methods. Ou…
DFlowSLAM: Self-Supervised Dynamic SLAM with Flow Motion Decomposition and DINO Guidance
Xingyuan Yu, Weicai Ye, Xiyue Guo +5
In this paper, we introduce a self-supervised deep SLAM method that robustly operates in dynamic scenes while accurately identifying dynamic components. Our method leverages a dual…
PVO: Panoptic Visual Odometry
Weicai Ye, Xinyue Lan, Shuo Chen +5
We present PVO, a novel panoptic visual odometry framework to achieve more comprehensive modeling of the scene motion, geometry, and panoptic segmentation information. Our PVO mode…
FD-SLAM: 3-D Reconstruction Using Features and Dense Matching
Xingrui Yang, Yuhang Ming, Zhaopeng Cui +1
It is well known that visual SLAM systems based on dense matching are locally accurate but are also susceptible to long-term drift and map corruption. In contrast, feature matching…
CGiS-Net: Aggregating Colour, Geometry and Implicit Semantic Features for Indoor Place Recognition
Yuhang Ming, Xingrui Yang, Guofeng Zhang +1
We describe a novel approach to indoor place recognition from RGB point clouds based on aggregating low-level colour and geometry features with high-level implicit semantic feature…
Object-Augmented RGB-D SLAM for Wide-Disparity Relocalisation
Yuhang Ming, Xingrui Yang, Andrew Calway
We propose a novel object-augmented RGB-D SLAM system that is capable of constructing a consistent object map and performing relocalisation based on centroids of objects in the map…