Three-dimensional medical image segmentation is critical for clinical diagnosis and treatment planning. Medical images typically exhibit heterogeneous characteristics of low inter-slice resolution and high in-plane resolution, leading 3D CNNs to lose...
Deep learning techniques are increasingly applied to point cloud semantic segmentation, where single-modal point cloud often suffers from accuracy-limiting confusion phenomena. Moreover, some networks with image and LiDAR data lack an efficient fusio...
This research presents an innovative technique for semantic segmentation of Hyperspectral Image (HSI) while focusing on its dimensionality reduction. A unique technique is applied to three distinct HSI landcover datasets, Indian Pines, Pavia Universi...
Precisely identifying and delineating food regions automatically from images, a task known as food image segmentation, is crucial for enabling applications in food science such as automated dietary logging, accurate nutritional analysis, and food saf...
Existing architecture semantic modeling methods in 3D complex urban scenes continue facing difficulties, such as limited training data, lack of semantic information, and inflexible model processing. Focusing on extracting and adopting accurate semant...
In precision agriculture, accurate, non-destructive estimation of fruit volume is crucial for quality grading, yield prediction, and post-harvest management. While vision-based methods provided some usefulness, fruits with complex geometry—such...
Background: Image-based dietary assessment provides a more intuitive approach for nutritional monitoring and health management. However, in multi-category bowl-based meals, food boundary adhesion, spatial stacking, and staple-food occlusion by upper-...
Exploring the relationships between plant phenotypes and genetic information requires advanced phenotypic analysis techniques for precise characterization. However, the diversity and variability of plant morphology challenge existing methods, which o...
Semantic segmentation is currently a hot topic in remote sensing image processing. There are extensive applications in land planning and surveying. Many current studies combine Convolutional Neural Networks (CNNs), which extract local information, wi...
Three-dimensional (3D) shape estimation of the human body has a growing number of applications in medicine, anthropometry, special effects, and many other fields. Therefore, the demand for the high-quality acquisition of a complete and accurate body...
Objective: Scaphoid fractures, particularly occult and non-displaced fractures, are difficult to detect using traditional X-ray methods because of their subtle appearance and variability in bone density. This study proposes a two-stage CNN approach t...
Post-disaster flexible suction requires perception of obstacle semantics and metric 3D geometry in cluttered, partially occluded workspaces. However, image-plane masks alone cannot provide physical height, surface slope, or obstacle clearance, while...
Obtaining consistent multi-view images of litchis is crucial for various litchi-related studies, such as data augmentation and 3D reconstruction. This paper proposes a two-stage model that integrates the Mask2Former semantic segmentation network with...
Accurately reconstructing tree skeletons from multi-view images is challenging. While most existing works use skeletonization from 3D point clouds, thin branches with low-texture contrast often involve multi-view stereo (MVS) to produce noisy and fra...
We propose a method to automatically detect 3D poses of closely interactive humans from sparse multi-view images at one time instance. It is a challenging problem due to the strong partial occlusion and truncation between humans and no tracking proce...
3D-dressed modelling has become a core technology in fashion design, digital human modelling, and virtual try-on applications. Existing image-based multi-view garment modelling methods primarily emphasise visual realism while often overlooking dimens...
Recognizing Manchu words can be challenging due to their complex character variations, subtle differences between similar characters, and homographic polysemy. Most studies rely on character segmentation techniques for character recognition or use co...
This letter presents the capabilities of a command line tool created to assess the quality of segmented digital images. The executable source code, called AssesSeg, was written in Python 2.7 using open source libraries. AssesSeg (University of Almeri...
The three-dimensional (3D) geometry reconstruction method utilizing ISAR image sequence energy accumulation (ISEA) shows great performance on triaxial stabilized space targets but fails when there is unknown motion from the target itself. The orthogo...
A timely and accurate damage assessment of buildings after an earthquake is critical for the safety of people and property. Most of the existing methods based on classification and segmentation use two-dimensional information to determine the damage...
Phenotypic traits of fungi and their automated extraction are crucial for evaluating genetic diversity, breeding new varieties, and estimating yield. However, research on the high-throughput, rapid, and non-destructive extraction of fungal phenotypic...
To address the inefficiency and unfairness of traditional manual scrap sorting, we propose the application of 3D vision technology for grading in this work. The multi-view 3D reconstruction algorithm achieves an accuracy within 1 mm in both synthetic...
3D reconstruction of construction scenes is an important enabling technology for digital and intelligent construction project management. Recurring foreground occluders and dynamic disturbances in tower-crane imagery can destabilize image registratio...
Semantic modeling is a challenging task that has received widespread attention in recent years. With the help of mini Unmanned Aerial Vehicles (UAVs), multi-view high-resolution aerial images of large-scale scenes can be conveniently collected. In th...
Egocentric multi-view image analysis refers to the processing of utilizing synchronized video streams captured from multiple wearable cameras worn on the head or body, providing complementary first-person perspectives of dynamic, real-world interacti...
Feature selection is a basic and important step in real applications, such as face recognition and image segmentation. In this paper, we propose a new weakly supervised multi-view feature selection method by utilizing pairwise constraints, i.e., the...
3D Gaussian Splatting (3DGS) enables real-time photorealistic scene reconstruction, yet its segmentation tasks suffer from two critical flaws: poor 3D consistency (e.g., blurred instance boundaries and unstable cross-view semantic association) and in...
Depth estimation is an active area of research in computer vision. When restricted to passive imaging, it is frequently approached as a stereo matching problem. Due to significant advancements in deep learning, stereo matching models have seen substa...
Multiple ocular diseases frequently coexist in fundus images, while image quality is highly susceptible to imaging conditions and patient cooperation, often manifesting as blurring, underexposure, and indistinct lesion regions. These challenges signi...
In order to improve the accuracy and real-time of image mosaic, realize the multi-view conveyor belt surface fault online detection, and solve the problem of longitudinal tear of conveyor belt, we in this paper propose an adaptive multi-view image mo...
Applying unmanned aerial vehicles (UAVs) and vision-based analysis methods to detect bridge surface damage significantly improves inspection efficiency, but the existing techniques have difficulty in accurately locating damage, making it difficult to...
The reliability of electric vehicle (EV) batteries requires detecting surface defects but also precisely locating them on the physical module for automated inspection, repair, and process optimisation. Conventional 2D computer vision methods, though...
Accurate segmentation of brain tumors from magnetic resonance 3D images (MRI) is critical for clinical decisions and surgical planning. Radiologists usually separate and analyze brain tumors by combining images of axial, coronal, and sagittal views....
Surface defect inspection of metallic lock components remains challenging due to strong specular reflections, low-contrast defect patterns, and geometric variability, which limit the consistency of manual inspection and conventional automated optical...
Using multi-view images of forest plots to reconstruct dense point clouds and extract individual tree parameters enables rapid, high-precision, and cost-effective forest plot surveys. However, images captured at close range face challenges in forest...
High-speed agile remote sensing satellites have the ability to capture multiple sequences of images. However, the frame rate is lower and the baseline between each image is much longer than normal image sequences. As a result, the edges and shadows i...
Accurate and reproducible quantitative assessment of cardiac size from thoracic radiographs remains challenging because conventional measurements require manual identification of multiple anatomical structures and geometric relationships. This study...
Nowadays, satellite image time series (SITS) analysis has become an indispensable part of many research projects as the quantity of freely available remote sensed data increases every day. However, with the growing image resolution, pixel-level SITS...
In low-altitude complex environments, accurately reconstructing the three-dimensional (3D) flight trajectories of small unmanned aerial vehicles (UAV) without onboard positioning modules remains challenging. To address this issue, this paper proposes...
This study introduces a versatile seed 3D reconstruction method that is applicable to multiple crops—including maize, wheat, and rice—and designed to overcome the inefficiency and subjectivity of manual measurements and the high costs of...
The generation of 3D digital humans has traditionally relied on multi-view imaging systems and large-scale datasets, posing challenges in cost, accessibility, and real-time applicability. To overcome these limitations, this study presents an efficien...
The key to semi-supervised semantic segmentation is to assign the appropriate pseudo-label to the pixels of unlabeled images. Recently, various approaches to consistency-based training and the filtering of reliable pseudo-labels have shown remarkable...
Due to the imbalance between urban and rural development and improper management, the spatial forms of many heritage villages have suffered severe damage, and their landscape styles are gradually being blurred, posing serious challenges to the protec...
A super multi-view (SMV) near-eye display (NED) effectively provides depth cues for three-dimensional (3D) display by projecting multiple viewpoint or parallax images onto the retina simultaneously. Previous SMV NED have suffered from a limited depth...
The phenotypic parameters of root systems are vital in reflecting the influence of genes and the environment on plants, and three-dimensional (3D) reconstruction is an important method for obtaining phenotypic parameters. Based on the characteristics...
Single-view RGB-D observations are often affected by occlusion and restricted viewpoints, leading to incomplete object geometry and underestimated obstacle extents in indoor robot perception. This paper proposes a single-view scene completion framewo...
Evaluating whether an intellectual property (IP) prototype faithfully preserves the visual identity and semantic intent of its original concept design is an important yet challenging task in product design and creative prototyping. Existing evaluatio...
This paper proposes a multi-sensor data-fusion-based method for real-scene 3D reconstruction and digital twin visualization of coal mine tunnels, aiming to address issues such as low accuracy in non-photorealistic modeling and difficulties in feature...
To completely comprehend neurodevelopment in healthy and congenitally abnormal fetuses, quantitative analysis of the human fetal brain is essential. This analysis requires the use of automatic multi-tissue fetal brain segmentation techniques. This pa...
Multi-view optical reconstruction supports spacecraft inspection, target characterization, and analysis from viewpoints not observed during image acquisition. For time-sensitive space situational awareness, such reconstruction must balance fidelity w...
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