As space technology advances, an increasing number of spacecrafts are being launched into space, making it essential to monitor and maintain satellites to ensure safe and stable operations. Acquiring 3D information of space targets enables the accura...
Close-range bridge inspection exposes personnel to risks associated with work at height and in confined spaces. Magnetic climbing robots can reduce this exposure, yet dense fastener groups and unsupported regions beyond truss member edges impose loca...
Novel view synthesis aims to generate new perspectives from a limited number of input views. Neural Radiance Field (NeRF) is a key method for this task, and it produces high-fidelity images from a comprehensive set of inputs. However, a NeRF’s...
Underwater visual perception is degraded by wavelength-dependent absorption and scattering, the effects of which vary with the camera-to-scene distance. Many underwater image enhancement methods nevertheless apply image-level transformations or use r...
Precise 3D perception is critical for indoor robotics, augmented reality, and autonomous navigation. However, existing multi-frame depth estimation methods often suffer from significant performance degradation in challenging indoor scenarios characte...
Accurate pear detection in complex orchard environments is essential for automated harvesting, yet it remains challenging due to frequent occlusion, overlapping fruits, cluttered backgrounds, and highly variable illumination. Although RGB-D sensing p...
This study examines how generative AI (GAI) impacts primary students’ in-depth learning, focusing on critical thinking and prior knowledge. A quasi-experiment involved 163 sixth-graders divided into three groups: a control group (lecture-based...
3D Gaussian Splatting (3DGS) is a multi-view 3D reconstruction method that relies solely on image loss for supervision, lacking explicit constraints on the geometric consistency of the rendering model. It uses a multi-view scene-by-scene training par...
Continuous tracking of individual fish provides a basis for movement analysis and visual monitoring in marine aquaculture. Underwater image degradation, similar appearance, and non-rigid motion complicate fish detection and identity preservation. Thi...
Accurate contour extraction of aggregate particles from conveyor-belt depth maps is essential for downstream particle counting and size measurement, yet industrial depth data often contains weak discontinuities, missing values, and speckle-like noise...
Existing 3D semantic scene reconstruction methods utilize the same set of features extracted from deep learning networks for both 3D semantic estimation and geometry reconstruction, ignoring the differing requirements of semantic segmentation and geo...
Monocular depth estimation (MDE) has emerged as a powerful technique for extracting scene depth from a single image, particularly in the context of computational imaging. Conventional MDE methods based on RGB images often degrade under varying illumi...
The application prospects of photorealistic 3D reconstruction are broad in smart cities, cultural heritage preservation, and related domains. However, existing methods face persistent challenges in balancing reconstruction accuracy, computational eff...
Depth super-resolution reconstructs high-resolution (HR) depth maps from low-resolution (LR) inputs with the aid of HR RGB guidance, but RGB edges often do not coincide with true depth discontinuities, causing texture copying and degraded geometric c...
Accurate estimation of atmospheric light (AL) is essential within the atmospheric scattering model (ASM) to achieve high-quality image dehazing. Most existing methods, however, typically assume spatial uniformity of AL and rely on heuristic estimatio...
Red–green–blue and depth (RGB-D) semantic segmentation combines appearance cues from RGB images with geometric information from depth maps, but sensor noise, missing measurements, and boundary-inconsistent depth responses can introduce co...
Neural radiation field (NeRF)-based novel view synthesis methods are gaining popularity. NeRF can generate more detailed and realistic images than traditional methods. Conventional NeRF reconstruction of a room scene requires at least several hundred...
Due to the rapid development of RGB-D sensors, increasing attention is being paid to depth image applications. Depth images play an important role in computer vision research. In this paper, we address the problem of inpainting for single depth image...
Image deraining holds great potential for enhancing the vision of autonomous vehicles in rainy conditions, contributing to safer driving. Previous works have primarily focused on employing a single network architecture to generate derained images. Ho...
Crown-level tree species semantic segmentation enables fine-grained forest inventory and management. Current high-precision tree species classification typically relies on multi-source remote sensing data, the acquisition and processing of which rema...
This study systematically investigates the laser surface hardening (LSH) behavior of two medium carbon steels—the low alloy 42CrMo4 and the plain carbon C45—using a 4 kW high power diode laser (HPDL). The influence of laser parameters (po...
To address the concerns of contrast deterioration, detail loss, and color distortion in images produced under haze conditions in scenarios such as intelligent driving and remote sensing detection, an algorithm for image defogging that combines Retine...
To address power transmission lines (PTLs) traveling through complex environments leading to misdetections and omissions in fitting recognition using cameras, we propose a fitting recognition approach combining depth-attention YOLOv5 and prior synthe...
Light field camera depth estimation is a core technology for high-precision three-dimensional reconstruction and realistic scene reproduction. We propose a depth estimation algorithm that fuses blurry features and planar geometric structure priors, a...
The response of the hypo-eutectoid steel to laser hardening, which is measured as the depth of the increased hardness, depends not only on the set of the process parameters but also on the prior microstructure of the workpiece. The multiple prelimina...
Single-view 3D reconstruction remains fundamentally ill-posed, as a single RGB image lacks scale and depth cues, often yielding ambiguous results under occlusion or in texture-poor regions. We propose DP-AMF, a novel Depth-Prior–Guided Adaptive...
Image inpainting is a crucial task in computer vision that aims to restore missing and occluded parts of damaged images. Deep-learning-based image inpainting methods have gained popularity in recent research. One such method is the deep image prior,...
Neural radiance fields (NeRFs) leverage a neural representation to encode scenes, obtaining photorealistic rendering of novel views. However, NeRF has notable limitations. A significant drawback is that it does not capture surface geometry and only r...
Neural radiation field (NeRF)-based novel view synthesis methods are gaining popularity for their ability to generate detailed and realistic images. However, most NeRF-based methods only use images to learn scene representations, ignoring the importa...
Three-view 3D Gaussian Splatting is prone to insufficient geometric constraints, overfitting to sparse color observations, and uneven allocation of Gaussian representation capacity, leading to structural distortions and local artifacts. We propose a...
Transformer-based detectors model long-range context effectively, yet their representations remain dominated by RGB appearance and can become unreliable in cluttered, occluded, or crowded scenes. We present BMF-DETR, a pseudo-depth-guided detector th...
Reflective low-pressure compressor blades produce missing and biased returns in low-cost depth cameras. CaM-PDA combines geometric anchor screening with prior-guided depth completion and residual experts for reflection, surface variation and boundari...
In this paper, the dehazing algorithm is proposed using a one-channel grayscale depth image generated from a LiDAR point cloud 2D projection image. In depth image-based dehazing, the estimation of the scattering coefficient is the most important. Sin...
We propose an online dehazing method with sparse depth priors using an incremental Gaussian Process (iGP). Conventional approaches focus on achieving single image dehazing by using multiple channels. In many robotics platforms, range measurements are...
Monocular RGB dense SLAM remains challenging because depth and global metric scale are not directly observable from a single camera. Existing systems often combine optical-flow and monocular-geometry priors predicted by independently trained networks...
Recently, self-supervised multi-view stereo (MVS) methods, which are dependent primarily on optimizing networks using photometric consistency, have made clear progress. However, the difference in lighting between different views and reflective object...
Underwater localization is one of the key techniques for positioning, navigation, timing (PNT) services that could be widely applied in disaster warning, underwater rescues and resource exploration. One of the reasons why it is difficult to achieve a...
Wear prediction for agricultural soil-engaging components is computationally demanding when discrete element method (DEM) simulations are repeatedly used for design evaluation and operating-parameter screening. In this study, an Archard-inspired Gaus...
To address the challenge of estimating the depth of a single-frequency (tonal) source using a vertical line array (VLA) without prior knowledge of seabed parameters, a method called OCMS-D (orthogonality-constrained modal search-based depth estimatio...
Underwater salient instance segmentation (USIS) remains challenging because color distortion, low contrast, and scattering often weaken appearance cues, while reliable geometric measurements are usually unavailable. Existing methods mainly rely on re...
Bishop Berkeley suggested that the distance of an object can be estimated if the object’s size is familiar to the observer. It has been suggested that humans can perceive the distance of the object by using such “familiarity” inform...
Depth completion aims to reconstruct dense depth maps from sparse LiDAR measurements guided by RGB images. Although BPNet enhanced depth structure perception through a bilateral propagation module and achieved state-of-the-art performance at the time...
Prior theory suggests a positive relation between volatility and market depth, while past empirical research finds contrasting results. This paper examines the relation between the volatility and the limit order book depth in commodity and foreign ex...
Generalizable 3D Gaussian Splatting enables efficient sparse-view novel view synthesis, but accurate Gaussian center estimation remains challenging. Epipolar attention and cost volume methods exhibit complementary limitations in non-Lambertian region...
Background: Personalized precision medicine has become a prevailing trend and applies to the selection of intraocular lenses (IOLs) for cataract surgery based on the unique corneal morphology of each person. The choice of presbyopia-correcting IOLs f...
Representing and rendering dynamic underwater scenes present significant challenges due to the medium’s inherent properties, which result in image blurring and information ambiguity. To overcome these challenges and accomplish real-time renderi...
Generating high-precision normalized digital surface models (nDSMs) from a single remote sensing image remains a challenging and ill-posed problem due to the absence of reliable geometric constraints. In this work, we show that monocular depth provid...
Depth-visualizing sensitivity can be degraded due to imperfect optical alignment and non-equidistant distribution of optical signals in the pixel array, which requires a measurement of the re-sampling process. To enhance this depth-visualizing sensit...
We used transient electromagnetic (TEM) to map the hydrogeological structures in the Choushui River Alluvial Fan in Yunlin County of central Taiwan. A total of 63 TEM measurements were collected using the FASTSNAP system with 50 × 50 m in-loop...
Recurring polarimetric radar signatures in supercells include deep and persistent differential reflectivity (ZDR) columns, hail inferred in low-level scans, and the ZDR arc signature. Prior investigations of supercell polarimetric signatures reveal p...
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