231 citations · 281 across the 12 of their papers we have counts for
12 papers
Terrain Perception for Agricultural UAVs in Complex Farmland via Rotating mmWave Radar
Zhihao Zhan, Le Tao, Shaobin Li +5
Accurate terrain perception is essential for terrain-following flight of agricultural unmanned aerial vehicles (UAVs), yet remains challenging in real-world farmland due to occlusi…
VFM-Recon: Unlocking Cross-Domain Scene-Level Neural Reconstruction with Scale-Aligned Foundation Priors
Yuhang Ming, Tingkang Xi, Xingrui Yang +4
Scene-level neural volumetric reconstruction from monocular videos remains challenging, especially under severe domain shifts. Although recent advances in vision foundation models…
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…
Benchmarking Neural Radiance Fields for Autonomous Robots: An Overview
Yuhang Ming, Xingrui Yang, Weihan Wang +4
Neural Radiance Fields (NeRF) have emerged as a powerful paradigm for 3D scene representation, offering high-fidelity renderings and reconstructions from a set of sparse and unstru…
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…
Vox-Surf: Voxel-based Implicit Surface Representation
Hai Li, Xingrui Yang, Hongjia Zhai +3
Virtual content creation and interaction play an important role in modern 3D applications such as AR and VR. Recovering detailed 3D models from real scenes can significantly expand…
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…
Real-Time Stereo Vision for Road Surface 3-D Reconstruction
Rui Fan, Yanan Liu, Xingrui Yang +3
Stereo vision techniques have been widely used in civil engineering to acquire 3-D road data. The two important factors of stereo vision are accuracy and speed. However, it is very…