Due to the difficulty in generating a 6-Degree-of-Freedom (6-DoF) object pose estimation dataset, and the existence of domain gaps between synthetic and real data, existing pose estimation methods face challenges in improving accuracy and generalizat...
The rapid evolution towards industrial automation has widened the usage of industrial applications, such as robot arm manipulation and bin picking. The performance of these applications relies on object detection and pose estimation through visual da...
Estimation and tracking of 6DoF poses of objects in images is a challenging problem of great importance for robotic interaction and augmented reality. Recent approaches applying deep neural networks for pose estimation have shown encouraging results....
Recently, 6DoF object pose estimation has become increasingly important for a broad range of applications in the fields of virtual reality, augmented reality, autonomous driving, and robotic operations. This task involves extracting the target area f...
Accurate pose estimation of non-cooperative space objects is crucial for applications such as satellite maintenance, space debris removal, and on-orbit assembly. However, monocular pose estimation methods face significant challenges in environments w...
Unmanned aerial vehicle (UAV) express delivery is facing a period of rapid development and continues to promote the aviation logistics industry due to its advantages of elevated delivery efficiency and low labor costs. Automatic detection, localizati...
Developing innovative and pervasive smart technologies that provide medical support and improve the welfare of the elderly has become increasingly important as populations age. Elderly people frequently experience incidents of discomfort in their dai...
Human pose estimation is a crucial task in computer vision with widespread applications in healthcare, rehabilitation, sports, and remote monitoring. In this paper, we propose a deep learning-based method for automatic human pose estimation and joint...
Recent advancements in deep learning techniques have accelerated the growth of robotic vision systems. One way this technology can be applied is to use a mobile robot to automatically generate a 3D map and identify objects within it. This paper addre...
Vehicle exterior inspection is a critical operation for identifying defects and ensuring the overall safety and integrity of vehicles. Visual-based inspection of moving objects, such as vehicles within dynamic environments abounding with reflections,...
Substations, as critical nodes for power transmission and distribution, play a pivotal role in ensuring the stability and security of the entire power grid. With the ever-increasing demand for electricity and the growing complexity of grid structures...
Three-dimensional object recognition is crucial in modern applications, including robotics in manufacturing, household items, augmented and virtual reality, and autonomous driving. Extensive research and numerous surveys have been conducted in this f...
Accurate estimation of 3D object pose is highly desirable in a wide range of applications, such as robotics and augmented reality. Although significant advancement has been made for pose estimation, there is room for further improvement. Recent pose...
In this paper, we propose two novel AR glasses pose estimation algorithms from single infrared images by using 3D point clouds as an intermediate representation. Our first approach “PointsToRotation” is based on a Deep Neural Network alone, whereas o...
The ability to obtain the 3D position of target vehicles is essential to managing and coordinating a multi-robot operation. We investigate an ML-backed object localization and tracking system to estimate the target’s 3D position based on a mono...
Poultry pose estimation is a prerequisite for evaluating abnormal behavior and disease prediction in poultry. Accurate pose-estimation enables poultry producers to better manage their poultry. Because chickens are group-fed, how to achieve automatic...
The analysis of hand–object poses from RGB images is important for understanding and imitating human behavior and acts as a key factor in various applications. In this paper, we propose a novel coarse-to-fine two-stage framework for hand–...
In this study, we propose a hybrid model for Perspective-n-Point (PnP)-based 6D object pose estimation called FusionNet that takes advantage of convolutional neural networks (CNN) and Transformers. CNN is an effective and potential tool for feature e...
Depth ambiguity is one of the main challenges of three-dimensional (3D) human pose estimation (HPE). The recent strategies of disambiguating have brought significant progress and remarkable breakthroughs in the field of 3D human pose estimation (3D H...
Transparent objects, commonly encountered in everyday environments, present significant challenges for 6D pose estimation due to their unique optical properties. The lack of inherent texture and color complicates traditional vision methods, while the...
The mushroom farming industry struggles to automate harvesting due to limited large-scale annotated datasets and the complex growth patterns of mushrooms, which complicate detection, segmentation, and pose estimation. To address this, we introduce a...
This paper presents a method for estimating the six Degrees of Freedom (6DoF) pose of texture-less objects from a monocular image by using edge information. The deep learning-based pose estimation method needs a large dataset containing pairs of an i...
Manipulation tasks on subsea instalments require extremely precise detection and localization of objects of interest. This problem is referred to as “pose estimation”. In this work, we present a framework for detecting and predicting 6DoF pose for re...
6DoF object pose estimation is a foundation for many important applications, such as robotic grasping, automatic driving, and so on. However, it is very challenging to estimate 6DoF pose of transparent object which is commonly seen in our daily life,...
The traditional estimation methods of space targets pose are based on artificial features to match the transformation relationship between the image and the object model. With the explosion of deep learning technology, the approach based on deep neur...
Pose estimation is an important task in the field of machine vision, being widely used in robot grasping, augmented reality, and other applications. Weakly textured objects pose severe challenges due to scarce texture and low-density features, becomi...
Deep learning has achieved great success on robotic vision tasks. However, when compared with other vision-based tasks, it is difficult to collect a representative and sufficiently large training set for six-dimensional (6D) object pose estimation, d...
6D object pose estimation is an essential component for robotic grasping. Most existing deep learning-based approaches focus on instance-level pose estimation, which requires prior object models and consequently limits their applicability on unseen o...
Contour shapes are important features. An accurate contour shape of a target can provide important prior information for applications, such as target recognition, which can improve the accuracy of target interpretation. In this paper, a synthetic ape...
In the agricultural sector, utilizing robots for tasks such as fruit harvesting poses significant challenges, particularly in achieving accurate 6D pose estimation of the target objects, which is essential for precise and efficient harvesting. Partic...
FusionNet is a hybrid model that incorporates convolutional neural networks and Transformers, achieving state-of-the-art performance in 6D object pose estimation while significantly reducing the number of model parameters. Our study reveals that Fusi...
This paper presents an experimental comparison between two existing methods representative of two categories of 6D pose estimation algorithms nowadays commonly used in the robotics community. The first category includes purely deep learning methods,...
To enhance the autonomy and flexibility of robotic systems, a crucial role is played by the capacity to perceive and grasp objects. More in detail, robot manipulators must detect the presence of the objects within their workspace, identify the graspi...
In this paper, we address the challenge of estimating the 6DoF pose of objects in 2D equirectangular images. This solution allows the transition to the objects’ 3D model from their current pose. In particular, it finds application in the educat...
In the industrial domain, estimating the pose of texture-less shiny parts is challenging but worthwhile. In this study, it is impractical to utilize texture information to obtain the pose because the features are likely to be affected by the surround...
Monocular six-degree-of-freedom (6-DoF) pose estimation of non-cooperative spacecraft is a fundamental technology for on-orbit servicing, space debris removal, and autonomous rendezvous and docking missions. Existing deep learning-based pose estimati...
Poultry managers can better understand the state of poultry through poultry behavior analysis. As one of the key steps in behavior analysis, the accurate estimation of poultry posture is the focus of this research. This study mainly analyzes a top-do...
Intelligent autonomous guided vehicles (AGVs) are of huge importance in facilitating the automation of load handling in the era of Industry 4.0. AGVs heavily rely on environmental perception, such as the 6D poses of objects, in order to execute compl...
Bin picking in industrial environments remains challenging due to the high cost of industrial 3D sensors and the typical requirement of structured-light projectors. We present Pickalo, a modular pipeline designed to reduce the setup complexity of ind...
In recent years, the benefits of both Augmented Reality (AR) technology and infrared thermography (IRT) have been demonstrated in the industrial maintenance sector, allowing maintenance operations to be carried out in a safer, faster, and more effici...
Six degrees of freedom (6-DoF) object pose estimation is essential for robotic grasping and autonomous driving. While estimating pose from a single RGB image is highly desirable for real-world applications, it presents significant challenges. Many ap...
Transformer architecture, initially developed for natural language processing and time series analysis, has been successfully adapted to various generative models in several domains. Object pose estimation, which uses images to determine the 3D posit...
The estimation of player positions is key for performance analysis in sport. In this paper, we focus on image-based, single-angle, player position estimation in padel. Unlike tennis, the primary camera view in professional padel videos follows a de f...
Image based human behavior and activity understanding has been a hot topic in the field of computer vision and multimedia. As an important part, skeleton estimation, which is also called pose estimation, has attracted lots of interests. For pose esti...
With the increasing importance of animal welfare, behavioral indicators such as changes in head and ear posture are widely recognized as non-invasive and field-applicable markers for evaluating the emotional state and stress levels of animals. Howeve...
Monocular depth estimation from Red-Green-Blue (RGB) images is a well-studied ill-posed problem in computer vision which has been investigated intensively over the past decade using Deep Learning (DL) approaches. The recent approaches for monocular d...
In this work, we address the problem of multi-vehicle detection and tracking for traffic monitoring applications. We preset a novel intelligent visual sensor for tracking-by-detection with simultaneous pose estimation. Essentially, we adapt an Extend...
Visual sorting of express parcels in complex scenes has always been a key issue in intelligent logistics sorting systems. With existing methods, it is still difficult to achieve fast and accurate sorting of disorderly stacked parcels. In order to ach...
In recent years, the breakthrough of neural networks and the rise of deep learning have led to the advancement of machine vision, which has been commonly used in the practical application of image recognition. Automobiles, drones, portable devices, b...
Head pose estimation is an important technology for analyzing human behavior and has been widely researched and applied in areas such as human–computer interaction and fatigue detection. However, traditional head pose estimation networks suffer...
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