231 citations · 303 across the 16 of their papers we have counts for
16 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…
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…
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…
Time-Frequency Jointed Imperceptible Adversarial Attack to Brainprint Recognition with Deep Learning Models
Hangjie Yi, Yuhang Ming, Dongjun Liu +1
EEG-based brainprint recognition with deep learning models has garnered much attention in biometric identification. Yet, studies have indicated vulnerability to adversarial attacks…
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…
EDI: ESKF-based Disjoint Initialization for Visual-Inertial SLAM Systems
Weihan Wang, Jiani Li, Yuhang Ming +1
Visual-inertial initialization can be classified into joint and disjoint approaches. Joint approaches tackle both the visual and the inertial parameters together by aligning observ…
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…
iDF-SLAM: End-to-End RGB-D SLAM with Neural Implicit Mapping and Deep Feature Tracking
Yuhang Ming, Weicai Ye, Andrew Calway
We propose a novel end-to-end RGB-D SLAM, iDF-SLAM, which adopts a feature-based deep neural tracker as the front-end and a NeRF-style neural implicit mapper as the back-end. The n…
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…