Stereoscopic Research Articles

Ultra‐High Secure Holographically Steganographic Array with Spatiotemporal Dual‐Encryption Keys

AbstractIndependently‐manipulated optical encryption has attracted great attention due to its high security and multiple application scenarios. Although photochromic molecules have become preferred holographic display units, the integration of dynamic modulation both in hologram and fluorescence for orthogonal encryption is still challenged. Herein, a latticed holographically steganographic array is constructed by incorporating a plasticizer (tri‐o‐cresyl phosphate, TOCP) into spirooxazine (SO) based polymers, thereby modulating the isomerization rate and the UV‐fluorescence kinetics between SO and merocyanine (MC). The period to reach fluorescence saturated value for each information bit in the latticed device can be widely modulated between 60 and 1700 s. Based on the property, only through ultraviolet stimulation can array information gradually be converted from spatial lattice coordinates to holographic display time. Then, a hidden 3D image can be determined from rapidly updatable reconstructed hologram video with refresh rate 1.125 Hz by the above spatiotemporal dual‐encryption keys. This work provides a bright path for the ultra‐high safety steganography and adaptive stereoscopic imaging.

In-depth morphological and functional analysis of ATTR-CA myocardial cells and niche by electron microscopic 3D reconstruction

Abstract Background Cell-cell interactions and interplay with extracellular matrix are known to be important in the steady state and pathological conditions, including wild-type transthyretin cardiac amyloidosis (wtATTR-CA). However, alterations of the microstructure of cardiomyocytes (CMs) and cardiac niches have not been well analyzed. Normal histological staining is usually limited in resolution, and 2D electron microscopy cannot capture stereoscopic images or the distribution of target particles and organelles in intra- and extracellular 3D space, so novel methods are being attempted. Methods and Results Using Serial Block Face-Scanning Electron Microscopy (SBF-SEM) and a 3D structural reconstruction system, we for the first time investigated the microstructure of human myocardial tissue from control hypertrophied heart (hypertensive heart disease) and wtATTR-CA patients. The microstructure of myocardial niche, cell morphology/numbers, and the distribution of intracellular organelles such as intercalated discs (ICDs) were compared to control endomyocardial biopsy (EMB) samples (2 controls vs 5 wtATTR-CA patients). In all wtATTR-CA samples, amyloid fibers were deposited originating around the capillary structures with various electron densities, compressing myocardial cells not only from the periphery but also dividing them from the center of the cell body, and CMs showed degeneration and dwarfing according to the severity of amyloid fiber deposition (Figure 1). The capillary structures showed degeneration and narrowing with stratified basement membrane, and rarefaction (3378±216.5 vs 1448±116.8/mm2, p<0.0001). Notably, the stromal cells (pericytes, fibroblasts, macrophages) were more likely buried by amyloid fibers than CMs, and their numbers were also reduced, indicating a loss of adjacent and intercellular interaction with capillaries and CMs (Fig. 2, 1892±194.4 vs 1189±107.4 mm2, p=0.0043). This method can also be used to analyze intracellular organelles and microstructures in CMs. In ATTR-CA, morphological abnormalities were observed in ICDs (Figure 3) and mitochondria. Conclusion In the ATTR-CM patients, there was a significant decrease in the number of capillaries in accordance with the deposition of myocardial amyloid fibers, as well as a decrease in stromal cells. These results support the hypothesis that amyloid fibril deposition not only causes chronic myocardial ischemia, but also reduces the number of niche cells, which play a supportive role for CM function and entirely exacerbate the damage. The SBF-SEM is an innovative tool for 3D imaging and quantitative analysis of myocardial ultrastructure and functions.Methods & Figure 1Figure 2 and Figure 3

A Pilot Study of Deep Learning-Based Monocular Depth Estimation from Fundus Photographs

The purpose of this study was to evaluate the feasibility of a generalizable deep-learning (DL) based system with no a priori knowledge of fundus photographs to generate monocular depth map information about optic disc structures from this imaging modality. Images of 30 stereo pairs of fundus photographs centered on the optic disc of 30 subjects were analyzed with this DL system to generate monocular depth maps using zero-shot cross-dataset transfer. These maps were registered onto reference standard depth maps derived from Optical Coherence Tomography. Accuracy of the DL system was assessed by the root of mean squared error (RMSE) between the estimate and reference standard. 47% of the total images from the dataset were successfully processed, with mean RMSE of 0.081. Our findings demonstrate that single image, monocular depth estimation with a generalizable DL system using zero-shot cross-dataset transfer applied to retinal color fundus photographs is feasible and has potential.

The Performance of the Optical Flow Field based Dense Image Matching for UAV Imagery

Abstract. With the rapid development of sensing platforms, unmanned aerial vehicle (UAV)-based mapping has become increasingly popular because of its economic efficiency and flexibility, especially for providing 3D information to support urban growth monitoring and change detection to meet sustainable development goals (SDGs). This paper presents an improved optical flow field-based dense matching algorithm (OFFDM) for low-altitude UAV images based on the Ph.D. thesis of Yuan (Yuan, 2018). First, high-precision seed points were used to compute the optical flow field within stereo pairs, effectively minimizing redundant calculations during the fine-matching phase. Second, a fine-matching approach, integrating multiple constraints, was applied to refine the coarse matching results based on the optical flow field. Extensive dense matching experiments on UAV low-altitude aerial imagery assessed the performance of OFFDIM across four dimensions: 3D point cloud visualization, matching success rate, precision, and reliability. Extensive experiments on low-altitude UAV imagery, characterized by a resolution of 7cm per pixel over a 10,608×8,608 pixel dimension and a 60% forward overlap, evaluate the OFFDM's efficacy. The quantitative evaluation revealed that the proposed method achieved an accuracy of ±0.7 pixels in image coordinates and ±20 cm on the ground, with a matching success rate exceeding 97%. The processing time was approximately 272 seconds for handling one single stereo pair. When compared to the widely adopted PMVS algorithm, known for its effectiveness in dense matching for UAV images, the proposed method demonstrated higher completeness and improved matching efficiency by more than five times. These results demonstrated that the proposed approach is more suitable for dense matching on UAV imagery-based high-precision 3D spatial data extraction, supporting global mapping tasks more effectively.

Retraction Note: Saliency detection in stereoscopic images using adaptive Gaussian Kernel and Gabor filter

Retraction Note: Saliency detection in stereoscopic images using adaptive Gaussian Kernel and Gabor filter

A Method for Tracking an Underwater Pipeline from Stereo Images Using an Autonomous Underwater Vehicle

The problem of tracking an underwater pipeline (UP) is considered in the context of an inspection mission. It is assumed that the diameter of the cylindrical pipe is known. To solve this problem, a tracking method is proposed, based on searching and calculating the center line of the UP, and determining the relative position of the autonomous underwater robot (AUV) and UP in the coordinate system of the AUV camera. Unlike well-known analogues, in which the solution is based on recognizing and constructing the boundaries of the UP in images, the proposed method searches for the true position of the center line of the UP on a set of possible options by checking their veracity. Possible options for the spatial position of the search centerline of the current UP section are generated by varying the direction of the beam in the horizontal and vertical plane. The starting point of the ray is the end point of the centerline of the previous section. The veracity criterion is to check that the 3D point features constructed in the scene belong to the cylindrical surface of the UP. The generation and matching of pointfeatures in images of a stereo pair is carried out using the SURF detector. The choice of the correct direction of the center line of the current UP section is ultimately made by voting. The end point of the center line of the current section is determined taking into account the calculated common visibility area with the previous section of the UP. To evaluate the effectiveness of the method, computational experiments were carried out on virtual scenes. The effectiveness was assessed by the accuracy of UP localization (in the AUV coordinate system) and by the speed of calculations in comparison with: a) the first version of this method, based on the use of a vectorized form of images; b) analogues using the Canny and Hough Transform detectors. The stability of the method to the accumulation of navigation accuracy errors during long-term tracking of UPs was also assessed.

Formability Characterization Using Curvature and Strain-Rate-Based Limit Strain Detection Methods Applied to Marciniak, Nakazima, and Stretch-Bend Tests

Despite advancements in the characterization of forming limit curves (FLCs) with the development of stereoscopic digital image correlation (DIC), there is still uncertainty in the accuracy of the limit strains, especially in forming operations with out-of-plane bending. The ISO12004-2:2008 standard offers a standardized approach to FLC determination but is not without limitations and is not always applicable to new materials and forming processes (e.g., warm forming, hot stamping). In the present work, a physically based limit strain detection technique is developed, termed the Enhanced Curvature Method (ECM), based on the sheet surface curvature evolution at the onset of necking in sheet formability testing. The ECM is applied to the characterization of 1.1 mm AA5182-O sheet using Marciniak, Nakazima, and stretch–bend characterization tests, and its limit strains are compared with those from the linear best-fit (LBF) local strain-rate approach and the ISO-12004 standard. The ECM considers the physical nature of necking in sheet forming with the aid of thresholds defined in terms of an imperfection metric analogous to the well-known Marciniak–Kuczynski (MK) imperfection factor. By quantifying the evolution of necking, FLCs of different safety margins can be readily generated, enabling a more intuitive selection for the factor of safety. For lower and upper ECM thresholds, the Marciniak plane strain limiting strain was determined to lie between 0.173 and 0.198, respectively, which is comparable to the analytical prediction of 0.194 and in general agreement with the published literature for AA5182-O. Similar plane strain limits were obtained using the ISO and LBF methods with values of 0.188 and 0.208, respectively. The same rankings in limit strain values between methods were observed for plane strain loading in Nakazima and stretch–bend tests.

Noise and inflow velocity measurements of fixed pitch rotors in edgewise flight

A common design of many of the proposed generation of electric Vertical Takeoff and Landing (eVTOL) vehicles involves fixed pitch rotors in edgewise flight. These applications typically have significantly lower tip Mach numbers than conventional rotor-craft and involve distributed smaller rotors making them operate at lower Reynolds numbers and hence likely having a greater sensitivity to gusts and environmental turbulence. This work will present results of studies with fixed pitch rotors conducted in the UF Anechoic Wind Tunnel Facility. The studies involve radiated noise, thrust and stereoscopic Particle Image Velocimetry to measure the inflow velocity to the rotor plane. The measurements were taken for un-altered free stream conditions as well as ones subjected to three different turbulence generation grids. The results provided show that there can be effects at moderate levels of free stream to turbulence to the rotor efficiency and radiated noise.

Stereoscopic depth perception through foliage

Both humans and computational methods struggle to discriminate the depths of objects hidden beneath foliage. However, such discrimination becomes feasible when we combine computational optical synthetic aperture sensing with the human ability to fuse stereoscopic images. For object identification tasks, as required in search and rescue, wildlife observation, surveillance, and early wildfire detection, depth assists in differentiating true from false findings, such as people, animals, or vehicles vs. sun-heated patches at the ground level or in the tree crowns, or ground fires vs. tree trunks. We used video captured by a drone above dense woodland to test users’ ability to discriminate depth. We found that this is impossible when viewing monoscopic video and relying on motion parallax. The same was true with stereoscopic video because of the occlusions caused by foliage. However, when synthetic aperture sensing was used to reduce occlusions and disparity-scaled stereoscopic video was presented, whereas computational (stereoscopic matching) methods were unsuccessful, human observers successfully discriminated depth. This shows the potential of systems which exploit the synergy between computational methods and human vision to perform tasks that neither can perform alone.

Passages

Peter Seibel's Coders at Work: Reflections on the Craft of Programming is 600-odd pages of extraordinary software engineering wisdom and insight. It is also self-contradictory; these pages often disagree with each other, and sometimes actually argue with each other. As Donald Knuth says, near the end of this book, "the key is usually to have a stereo view instead of a one-dimensional view."

Experimental characterization of coherent states in turbulent magnetohydrodynamic pipe flow

Investigating magnetohydrodynamic (MHD) flows, whether through experimental or numerical study, presents significant challenges. A minimum requirement for experimentally studying MHD flows using optical measurement methods is the use of highly conductive, transparent fluids and strong magnetic fields in close proximity to the flow confinement. In response to these complexities, this work introduces a large-scale pipe rig setup, integrating a magnetic frame structure with a Stereoscopic Particle Image Velocimetry system for MHD flow field characterizations. This allows for the detailed analysis of coherent flow patterns under conditions of fully developed MHD turbulence. In alignment with earlier numerical studies on turbulent MHD pipe flow, our research confirms that low Hartmann number turbulence statistics are minimally affected by the applied magnetic field. Nevertheless, we show that the magnetic field significantly extends the streamwise extent of detected coherent organizational states, while their wave number distribution and morphology largely remain unchanged.

Evaluation of the different methods of optic disc examination in glaucomatous patients

Background Glaucoma is a leading cause of blindness worldwide. Many patients discover glaucoma accidentally during regular checkups. Purpose To evaluate the agreement using slit lamp biomicroscopy, stereoscopic fundus photography, and optical coherence tomography (OCT) in the evaluation of the optic disc area, the cup area, and the vertical cup disc ratio (VCDR) in glaucomatous patients. Patients and methods This cross-sectional observational study includes 28 eyes of glaucomatous patients. All patients underwent slit lamp biomicroscopy using a +90 D lens, stereoscopic fundus photography using a computerized program to measure the optic disc parameters, and OCT for optic disc evaluation. Three examiners did the analysis. Results Comparing results obtained on stereoscopic fundus photography and OCT, examiner one reported moderate reliability regarding disc area, cup area, and the VCDR with an intraclass coefficient (ICC) of 0.67, 0.67, and 0.50 and P values of 0.68, 0.61, and 0.01, respectively. Examiner two reported moderate reliability regarding disc area, cup area, and VCDR with an ICC of 0.66, 0.63, and 0.54 and P values of 0.16, 0.69, and 0.03, respectively. Examiner three reported moderate reliability regarding disc area and VCDR with an ICC of 0.65, 0.71, and P values of 0.69 and 0.07, respectively. A good reliability for the cup area was reported with an ICC of 0.82 and a P value of 0.02. The slit lamp and stereoscopic fundus photos showed moderate reliability compared with fundus photography values. Conclusion There is an agreement between values obtained by slit lamp biomicroscopy, stereoscopic fundus photography, and OCT.

Tracking 3D motion of instruments in microsurgery: A comparative study of stereoscopic marker-based vs. deep learning method for objective analysis of surgical skills

Background:In microsurgery, integrating motor and visual information is crucial for achieving precise bimanual maneuvers. Computer vision serves as a useful tool for analyzing surgical maneuvers and enhancing situational awareness in medical assistive systems. Furthermore, the combination of deep learning with computer vision shows promise for objectively assessing surgical skills. Methods:This study compared two methods for tracking 3D movement during microsurgery: Mitracks3D, a stereoscopic tracker using color-marked instruments, and a deep learning method for instruments identification based on YOLOv8. Additionally, drawing an analogy between single-camera and new stereoscopic recording systems, 2D and 3D motion signals from microsurgery training videos on the peg transfer task were obtained to analyze surgeons’ psychomotor skills using six motion analysis parameters (MAPs). Results:When comparing the two 3D tracking methods, the motion signals revealed a relative error (ϵ) of less than 10%, with a correlation coefficient (ρ) exceeding 0.9892 ±0.0020, tracking loss below 2.0398%, and instruments detection time under 1 ms for Mitracks3D and 7.09 ±0.62 ms for YOLOv8. When comparing the performance between participants using 2D and 3D signals, statistically significant differences were found in 4 of the 6 explored MAPs. Additionally, a high cosine similarity (cs>0.99) was found between the performance scores of the 6 MAPs, indicating compatibility between the 2D and 3D recording modalities. Conclusions:The deep learning-based approach is as effective as stereo-tracking with markers; both methods produced remarkably similar 3D motion signals. The compatibility in evaluation between 2D and 3D was confirmed. In essence, adopting computer vision methods such as Mitracks3D and YOLOv8 provides a compelling alternative for constructing objective assessment tools for surgical skills.

Swirl-induced hysteresis in a sudden expansion flow

Swirling sudden expansion flows are complex flow fields containing several coherent structures that depend on the swirl number and can exhibit hysteresis behavior between increasing and subsequently decreasing swirl levels. While these flows have extensively been studied in simple geometries, results involving special designed nozzles are scarce. Therefore, this paper aims to provide insights into a more complex geometry, specifically a two-step conical expansion with a converging outlet. Experimental data is acquired for changing swirl numbers at a Reynolds number in the range of 35, 000. Stereoscopic Particle Image Velocimetry is employed to characterize downstream flow structures, while Laser Doppler Velocimetry is used to characterize upstream structures and to determine the inlet swirl number. Several distinct flow patterns are found as a function of the swirl number and the identified flow patterns include, in order of increasing swirl, a Closed Jet Flow, an Open Jet Flow (OJF), and a Coandã Jet Flow (CoJF). A central positive axial velocity is noted for both OJF and CoJF downstream of the expansion due to the converging outlet geometry. At higher swirl numbers, Vortex Breakdown moves upstream into the nozzle until a negative axial velocity is noted in the inlet tube. For these higher swirl numbers, no hysteresis is observed in the inlet tube between increasing and subsequently decreasing swirl. However, downstream of the nozzle, it is observed that the CoJF detaches at a lower swirl number than the swirl number required for attachment, indicating a hysteresis effect between in- and decreasing swirl.

Flow field and emission characterization of a novel enclosed jet-in-hot-coflow canonical burner

The jet-in-hot-coflow is a canonical combustion setup, which has been used in several studies to study Flameless/MILD combustion and auto-ignition of fuels. However, the NOx and CO emission measurements from these combustion setups were not possible due to the entrainment of laboratory air and a lack of a well-defined physical system limit. These limitations have been overcome by a new enclosed jet-in-hot-coflow setup. The combustor was operated by injecting a mixture of CH4-Air in the central jet, and the coflow comprised of hot products from CH4-Air combustion in burners upstream. The coflow composition was further controlled by adding diluents such as N2 and CO2. Measurements were done using stereoscopic particle image velocimetry, suction probe gas analysis, thermocouples, and chemiluminescence imaging. Increasing central jet velocity and equivalence ratio led to lower NOx and a reaction zone that enlarged and shifted downstream. The reduction in NOx emission was attributed to the returning mechanism. Adding CO2 and N2 as diluents in the coflow resulted in a longer combustion zone and reduced temperatures in the combustion chamber, leading to decreased NOx production and increased reburning. These experiments provide relevant flowfield and emissions data for modelers and help characterize combustion regimes such as Flameless/MILD.

Full-Body Pose Estimation of Humanoid Robots Using Head-Worn Cameras for Digital Human-Augmented Robotic Telepresence

We envision a telepresence system that enhances remote work by facilitating both physical and immersive visual interactions between individuals. However, during robot teleoperation, communication often lacks realism, as users see the robot’s body rather than the remote individual. To address this, we propose a method for overlaying a digital human model onto a humanoid robot using XR visualization, enabling an immersive 3D telepresence experience. Our approach employs a learning-based method to estimate the 2D poses of the humanoid robot from head-worn stereo views, leveraging a newly collected dataset of full-body poses for humanoid robots. The stereo 2D poses and sparse inertial measurements from the remote operator are optimized to compute 3D poses over time. The digital human is localized from the perspective of a continuously moving observer, utilizing the estimated 3D pose of the humanoid robot. Our moving camera-based pose estimation method does not rely on any markers or external knowledge of the robot’s status, effectively overcoming challenges such as marker occlusion, calibration issues, and dependencies on headset tracking errors. We demonstrate the system in a remote physical training scenario, achieving real-time performance at 40 fps, which enables simultaneous immersive and physical interactions. Experimental results show that our learning-based 3D pose estimation method, which operates without prior knowledge of the robot, significantly outperforms alternative approaches requiring the robot’s global pose, particularly during rapid headset movements, achieving markerless digital human augmentation from head-worn views.

Learning Domain Invariant Features for Unsupervised Indoor Depth Estimation Adaptation

Predicting depth maps from monocular images has made an impressive performance in the past years. However, most depth estimation methods are trained with paired image-depth map data or multi-view images (e.g., stereo pair and monocular sequence), which suffer from expensive annotation costs and poor transferability. Although unsupervised domain adaptation methods are introduced to mitigate the reliance on annotated data, rare works focus on the unsupervised cross-scenario indoor monocular depth estimation. In this article, we propose to study the generalization of depth estimation models across different indoor scenarios in an adversarial-based domain adaptation paradigm. Concretely, a domain discriminator is designed for discriminating the representation from source and target domains, while the feature extractor aims to confuse the domain discriminator by capturing domain-invariant features. Further, we reconstruct depth maps from latent representations with the supervision of labeled source data. As a result, the feature extractor learned features possess the merit of both domain-invariant and low source risk, and the depth estimator can deal with the domain shift between source and target domains. We conduct the cross-scenario and cross-dataset experiments on the ScanNet and NYU-Depth-v2 datasets to verify the effectiveness of our method and achieve impressive performance.

Flow Field Characteristics at the Spanwise Edge of a Vegetative Canopy Model

This study investigates the complex flow field across a spanwise vegetative model canopy edge focusing on turbulent transport processes. Utilizing stereoscopic particle image velocimetry, the three velocity components were measured in wall-parallel planes at various elevations within canopy across the spanwise canopy edge. Conventional ensemble averaged results were contrasted with those obtained by conditionally averaged flow properties across instantaneous internal interfaces in the flow to understand their contribution to the ensemble average. The conditional average captured the strong gradients in mean velocities, Reynolds stresses, vorticity, swirling strength, and turbulent kinetic energy production across the dynamically changing instantaneous interface. In contrast, the conventional ensemble average smeared out the strong gradients. Small magnitudes of advective terms in the turbulent kinetic energy transport equation suggested weak secondary transverse flows in the present model canopy. The turbulent flow structure across the spanwise canopy edge was further investigated using Quadrant-Hole analysis for both averaging approaches. Conventional ensemble averaged results indicated a shift from sweep to ejection dominance when moving from canopy into the open patch, while the conditional average showed only sweep dominated transport. In contrast to a homogeneous canopy layout, below canopy height at the canopy edge, sweeps and ejections lose their dominance in vertical turbulent transport. The present results show that the dynamics of internal interfaces govern the ensemble averaged results and a possible implementation into existing models is proposed. The present results are expected to increase understanding of spanwise turbulent transport and aid in developing strategies to mitigate desertification.

Is It Reliable to Extract Gully Morphology Parameters Based on High-Resolution Stereo Images? A Case of Gully in a “Soil-Rock Dual Structure Area”

The gully morphology parameter is an important quantitative index for monitoring gully erosion development. Its extraction method and accuracy evaluation in the “soil-rock dual structure area” are of great significance to the evaluation of gully erosion in this type of area. In this study, unmanned aerial vehicle (UAV) tilt photography data were used to evaluate the accuracy of extracting gully morphology parameters from high-resolution remote sensing stereoscopic images. The images data (0.03 m) were taken as the reference in Zhangmazhuang and Jinzhongyu small river valleys in Yishui County, Shandong Province, China. The accuracy of gully morphology parameters were extracted from simultaneous high-resolution remote sensing stereo images data (0.5 m) was evaluated, and the parameter correction model was constructed. The results showed that (1) the average relative errors of circumference (P), area (A), linear length of bottom (L1), and curve length of bottom (L2) are mainly concentrated within 10%, and the average relative errors of top width (TW) are mainly within 20%. (2) The average relative error of three-dimensional (3D) parameters such as gully volume (V) and gully depth (D) is mainly less than 50%. (3) The larger the size of the gully, the smaller the 3D parameters extracted by visual interpreters, especially the absolute value of the mean relative error (Rmean) of V and D. (4) A relationship model was built between the V and D values obtained by the two methods. When V and D were extracted from high-resolution remote sensing stereo images, the relationship model was used to correct the measured parameter values. These findings showed that high-resolution remote sensing stereo images represents an efficient and convenient data source for monitoring gully erosion in a small watershed in a “soil-rock dual structure area”.

Weakly-supervised Depth Estimation and Image Deblurring via Dual-Pixel Sensors.

Dual-pixel (DP) imaging sensors are getting more popularly adopted by modern cameras. A DP camera captures a pair of images in a single snapshot by splitting each pixel in half. Several previous studies show how to recover depth information by treating the DP pair as an approximate stereo pair. However, dual-pixel disparity occurs only in image regions with defocus blur which is unlike classic stereo disparity. Heavy defocus blur in DP pairs affects the performance of depth estimation approaches based on matching. Therefore, we treat the blur removal and the depth estimation as a joint problem. We investigate the formation of the DP pair, which links the blur and depth information, rather than blindly removing the blur effect. We propose a mathematical DP model that can improve depth estimation by the blur. This exploration motivated us to propose our previous work, an end-to-end DDDNet (DP-based Depth and Deblur Network), which jointly estimates depth and restores the image in a supervised fashion. However, collecting the ground-truth (GT) depth map for the DP pair is challenging and limits the depth estimation potential of the DP sensor. Therefore, we propose an extension of the DDDNet, called WDDNet (Weakly-supervised Depth and Deblur Network), which includes an efficient reblur solver that does not require GT depth maps for training. To achieve this, we convert all-in-focus images into supervisory signals for unsupervised depth estimation in our WDDNet. We jointly estimate an all-in-focus image and a disparity map, then use a Reblur and Fstack module to regularize the disparity estimation and image restoration. We conducted extensive experiments on synthetic and real data to demonstrate the competitive performance of our method when compared to state-of-the-art (SOTA) supervised approaches. Index Terms-Dual-pixel Sensor, Weakly-supervised, Depth Estimation, Deblur and Reblu.