Semantic segmentation of the sensed point cloud data plays a significant role in scene understanding and reconstruction, robot navigation, etc. This work presents a Graph Convolutional Network integrating K-Nearest Neighbor searching (KNN) and Vector...
The goal of visual place recognition (VPR) is to determine the location of a query image by identifying its place in a collection of image databases. Visual sensor technologies are crucial for visual place recognition as they allow for precise identi...
Vector of locally aggregated descriptor (VLAD) coding has become an efficient feature coding model for retrieval and classification. In some recent works, the VLAD coding method is extended to a deep feature coding model which is called NetVLAD. NetV...
Many place recognition approaches, which identify previously visited places or locations by matching current sensory data, such as 2D RGB images and 3D point clouds, have been proposed to achieve accurate and robust localization and loop closure dete...
In dynamic environments, convolutional neural networks (CNNs) often produce image feature maps with significant redundancy due to external factors such as moving objects and occlusions. These feature maps are inadequate as precise image descriptors f...
In autonomous driving scenarios, the presence of dynamic objects can significantly degrade the precision and recall of loop-closure detection. To further improve robustness, this paper proposes a loop-closure detection framework with dynamic-object s...
Accurate identification of insect pests is the key to improve crop yield and ensure quality and safety. However, under the influence of environmental conditions, the same kind of pests show obvious differences in intraclass representation, while the...
Visual Place Recognition (VPR) addresses visual instance retrieval tasks against discrepant scenes and gives precise localization. During a traverse, the captured images (query images) would be traced back to the already existing positions in the dat...
LiDAR-based place recognition is critical for long-term autonomous navigation in Global Navigation Satellite System (GNSS)-denied environments, yet existing methods struggle to balance accuracy and efficiency under substantial yaw rotations. This pap...
In response to the inaccurate positioning of traditional camera relocation methods in scenes with large-scale or severe viewpoint changes, this study proposes a camera relocation method based on a cascaded graph neural network to achieve accurate sce...
Accurate localization between cameras is a prerequisite for a vision-based heterogeneous robot systems task. The core issue is how to accurately perform place recognition from different view-points. Traditional appearance-based methods have a high pr...
LiDAR-based place recognition (LPR) is crucial for the navigation and localization of autonomous vehicles and mobile robots in large-scale outdoor environments and plays a critical role in loop closure detection for simultaneous localization and mapp...
Loop closure detection is an important component of Simultaneous Localization and Mapping (SLAM). In this paper, a novel two-branch loop closure detection algorithm unifying deep Convolutional Neural Network (ConvNet) features and semantic edge featu...
In recent years, semantic segmentation has made significant progress in visual place recognition (VPR) by using semantic information that is relatively invariant to appearance and viewpoint, demonstrating great potential. However, in some extreme sce...
Decorative openwork windows (DO-Ws) in Suzhou traditional private gardens play a vital role in Chinese traditional garden art. Due to the delicate and elegant patterns, as well as their rich cultural meaning, DO-Ws have quite high protection and util...
Thermal infrared imaging is attracting much attention due to its strength against illuminance variation. However, because of the spectral difference between thermal infrared images and RGB images, the existing research on self-supervised monocular de...
Emotion is a form of high-level paralinguistic information that is intrinsically conveyed by human speech. Automatic speech emotion recognition is an essential challenge for various applications; including mental disease diagnosis; audio surveillance...
Continual LiDAR place recognition requires a descriptor model to learn new environments while retaining retrieval accuracy in previously learned environments under limited access to historical data. Replaying historical retrieval relations and distil...
Accurate estimation of an object’s 6D pose is one of the crucial technologies for robotic manipulators. Especially when the lighting conditions changes or the object is occluded, resulting in the missing or the interference of the object inform...
Deep convolutional neural networks (DCNNs) with alternating convolutional, pooling and decimation layers are widely used in computer vision, yet current works tend to focus on deeper networks with many layers and neurons, resulting in a high computat...