Training-Free Instance Segmentation from Semantic Image Segmentation Masks

In recent years, the development of instance segmentation has garnered significant attention in a wide range of applications. However, the training of a fully-supervised instance segmentation model requires costly both instance-level and pixel-level annotations. In contrast, weakly-supervised instance segmentation methods (i.e., with image-level class labels or point labels) struggle to satisfy the accuracy and recall requirements of practical scenarios. In this paper, we propose a novel paradigm for instance segmentation called training-free instance segmentation (TFISeg), which achieves instance segmentation results from image masks predicted using off-the-shelf semantic segmentation models. TFISeg does not require training a semantic or/and instance segmentation model and avoids the need for instance-level image annotations. Therefore, it is highly efficient. Specifically, we first obtain a semantic segmentation mask of the input image via a trained semantic segmentation model. Then, we calculate a displacement field vector for each pixel based on the segmentation mask, which can indicate representations belonging to the same class but different instances, i.e., obtaining the instance-level object information. Finally, instance segmentation results are obtained after being refined by a learnable category-agnostic object boundary branch. Extensive experimental results on two challenging datasets and representative semantic segmentation baselines (including CNNs and Transformers) demonstrate that TFISeg can achieve competitive results compared to the state-of-the-art fully-supervised instance segmentation methods without the need for additional human resources or increased computational costs. The code is available at: TFISegComment: 14 pages,5 figure

Accelerated Li⁺ Desolvation for Diffusion Booster Enabling Low‐Temperature Sulfur Redox Kinetics via Electrocatalytic Carbon‐Grazfted‐CoP Porous Nanosheets

Lithium–sulfur (Li–S) batteries are famous for their high energy density and low cost, but prevented by sluggish redox kinetics of sulfur species due to depressive Li ion diffusion kinetics, especially under low-temperature environment. Herein, a combined strategy of electrocatalysis and pore sieving effect is put forward to dissociate the Li+ solvation structure to stimulate the free Li+ diffusion, further improving sulfur redox reaction kinetics. As a protocol, an electrocatalytic porous diffusion-boosted nitrogen-doped carbon-grafted-CoP nanosheet is designed via forming the NCoP active structure to release more free Li+ to react with sulfur species, as fully investigated by electrochemical tests, theoretical simulations and in situ/ex situ characterizations. As a result, the cells with diffusion booster achieve desirable lifespan of 800 cycles at 2 C and excellent rate capability (775 mAh g−1 at 3 C). Impressively, in a condition of high mass loading or low-temperature environment, the cell with 5.7 mg cm−2 stabilizes an areal capacity of 3.2 mAh cm−2 and the charming capacity of 647 mAh g−1 is obtained under 0 °C after 80 cycles, demonstrating a promising route of providing more free Li ions toward practical high-energy Li–S batteries

The 3rd Anti-UAV Workshop & Challenge: Methods and Results

The 3rd Anti-UAV Workshop & Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UAV Challenge has been publicly released. There are two main differences between this year's competition and the previous two. First, we have expanded the existing dataset, and for the first time, released a training set so that participants can focus on improving their models. Second, we set up two tracks for the first time, i.e., Anti-UAV Tracking and Anti-UAV Detection & Tracking. Around 76 participating teams from the globe competed in the 3rd Anti-UAV Challenge. In this paper, we provide a brief summary of the 3rd Anti-UAV Workshop & Challenge including brief introductions to the top three methods in each track. The submission leaderboard will be reopened for researchers that are interested in the Anti-UAV challenge. The benchmark dataset and other information can be found at: https://anti-uav.github.io/.Comment: Technical report for 3rd Anti-UAV Workshop and Challenge. arXiv admin note: text overlap with arXiv:2108.0990

Innovative Rotating SAR Mode for 3D Imaging of Buildings

Three-dimensional SAR imaging of urban buildings is currently a hotspot in the research area of remote sensing. Synthetic Aperture Radar (SAR) offers all-time, all-weather, high-resolution capacity, and is an important tool for the monitoring of building health. Buildings have geometric distortion in conventional 2D SAR images, which brings great difficulties to the interpretation of SAR images. This paper proposes a novel Rotating SAR (RSAR) mode, which acquires 3D information of buildings from two different angles in a single rotation. This new RSAR mode takes the center of a straight track as its rotation center, and obtains images of the same facade of a building from two different angles. By utilizing the differences in geometric distortion of buildings in the image pair, the 3D structure of the building is reconstructed. Compared to the existing tomographic SAR or circular SAR, this method does not require multiple flights in different elevations or observations from varying aspect angles, and greatly simplifies data acquisition. Furthermore, both simulation analysis and actual data experiment have verified the effectiveness of the proposed method

Enhancing SAR Multipath Ghost Image Suppression for Complex Structures through Multi-Aspect Observation

When Synthetic Aperture Radar (SAR) observes complex structural targets such as oil tanks, it is easily interfered with by multipath signals, resulting in a large number of multipath ghost images in the SAR image, which seriously affect the image clarity. To address this problem, this paper proposes a multi-aspect multipath suppression method. This method observes complex structural targets from different azimuth angles to obtain a multi-aspect image sequence and then uses the difference in sequence features between the target image and the multipath ghost image with respect to aspect angle to separate them. This paper takes a floating-roof oil tank as an example to analyze the propagation path and the ghost image characteristics of multipath signals under different observation aspects. We conclude that the scattering center of the multipath ghost image changes with the radar observation aspect, whereas the scattering center of the target image does not. This paper uses the Robust Principal Component Analysis (RPCA) method to decompose the image sequence matrix into two parts: a sparse matrix and a low-rank matrix. The low-rank matrix represents the aspect-stable principal component in the image sequence; that is, the real scattering center. The sparse matrix represents the part of the image sequence that deviates from the principal component; that is, the signal that varies with aspect, mainly including multipath signals, sidelobes, anisotropic signals, etc. By reconstructing the low-rank matrix and the sparse matrix, respectively, we can obtain the image after multipath signal suppression and also the multipath ghost image. Both the target and the multipath signal provide useful information. The image after multipath signal suppression is useful for obtaining the structural information of the target, and the multipath ghost image is useful for analyzing the multipath phenomenon of the complex structure target. This paper conducts experimental verification using real airborne SAR data of an external floating roof oil tank and compares three methods: RPCA, PCA, and sub-aperture fusion method. The experiment shows that the RPCA method can better separate the target image and the multipath ghost image

SAR Multi-Angle Observation Method for Multipath Suppression in Enclosed Spaces

Synthetic aperture radar (SAR) is a powerful tool for detecting and imaging targets in enclosed environments, such as tunnels and underground garages. However, SAR performance is degraded by multipath effects, which occur when electromagnetic waves are reflected by obstacles, such as walls, and interfere with the direct signal. This results in the formation of multipath ghost images, which obscure the true target and reduce the image quality. To overcome this challenge, we propose a novel method based on multi-angle observation. This method exploits the fact that the position of ghost images changes depending on the angle of the radar, while the position of the true target remains stable. By collecting and processing multiple data sets from different angles, we can eliminate the ghost images and enhance the target image. In addition, we introduce a center vector distance algorithm to address the complexity and computational intensity of existing multipath suppression algorithms. This algorithm, which defines the primary direction of multi-angle vectors from stable scattering centers as the center vector, processes and synthesizes multiple data sets from multi-angle observations. It calculates the distance of pixel intensity sequences in the composite data image from the center vector. Pixels within a specified threshold are used for imaging, and the final result is obtained. Simulation experiments and real SAR data from underground garages confirm the effectiveness of this method in suppressing multipath ghost images

Ni3+-Induced Hole States Enhance the Oxygen Evolution Reaction Activity of NixCo3- xO4 Electrocatalysts

This work reports a systematical study on the relationship of electronic structure to oxygen evolution reaction (OER) activity of NixCo3-xO4 (x = 0-1) mixed oxides. The specific OER activity is substantially increased by 16 times from 0.02 mA cm-2 BET for pure Co3O4 to 0.32 mA cm-2 BET for x = 1 at an overpotential of 0.4 V and exhibits a strong correlation with the amount of Ni ions in the +3 oxidation state. X-ray spectroscopic study reveals that inclusion of Ni3+ ions upshifts the occupied valence band maximum (VBM) by 0.27 eV toward the Fermi level (EF), and creates a new hole (unoccupied) state located ∼1 eV above the EF. Such electronic features favor the adsorption of OH surface intermediates on NixCo3-xO4, resulting in enhanced OER. Furthermore, the emerging hole state effectively reduces the energy barrier for electron transfer from 1.19 to 0.39 eV, and thereby improves the kinetics for OER. The electronic structure features that lead to a higher OER in NixCo3-xO4 can be extended to other transition metal oxides for rational design of highly active catalysts

Ni\u3csup\u3e3+\u3c/sup\u3e-Induced Hole States Enhance the Oxygen Evolution Reaction Activity of Ni\u3csub\u3ex\u3c/sub\u3eCo\u3csub\u3e3- x\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e Electrocatalysts

\u3cp\u3eThis work reports a systematical study on the relationship of electronic structure to oxygen evolution reaction (OER) activity of Ni\u3csub\u3ex\u3c/sub\u3eCo\u3csub\u3e3-x\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e (x = 0-1) mixed oxides. The specific OER activity is substantially increased by 16 times from 0.02 mA cm\u3csup\u3e-2\u3c/sup\u3e \u3csub\u3eBET\u3c/sub\u3e for pure Co\u3csub\u3e3\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e to 0.32 mA cm\u3csup\u3e-2\u3c/sup\u3e \u3csub\u3eBET\u3c/sub\u3e for x = 1 at an overpotential of 0.4 V and exhibits a strong correlation with the amount of Ni ions in the +3 oxidation state. X-ray spectroscopic study reveals that inclusion of Ni\u3csup\u3e3+\u3c/sup\u3e ions upshifts the occupied valence band maximum (VBM) by 0.27 eV toward the Fermi level (E\u3csub\u3eF\u3c/sub\u3e), and creates a new hole (unoccupied) state located ∼1 eV above the E\u3csub\u3eF\u3c/sub\u3e. Such electronic features favor the adsorption of OH surface intermediates on Ni\u3csub\u3ex\u3c/sub\u3eCo\u3csub\u3e3-x\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e, resulting in enhanced OER. Furthermore, the emerging hole state effectively reduces the energy barrier for electron transfer from 1.19 to 0.39 eV, and thereby improves the kinetics for OER. The electronic structure features that lead to a higher OER in Ni\u3csub\u3ex\u3c/sub\u3eCo\u3csub\u3e3-x\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e can be extended to other transition metal oxides for rational design of highly active catalysts.\u3c/p\u3

Tailoring the Electronic Structures of the La2NiMnO6Double Perovskite as Efficient Bifunctional Oxygen Electrocatalysis

Double perovskite oxides are one of the most promising bifunctional electrocatalysts for efficient oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) due to their adjustable electronic structures via doping with different metal cations or engineering of defects. Herein, we report a systematic study on the tuning of the electronic structure of La2-xSrxNiMnO6 with 0 ≤ x ≤ 1.0 to promote the bifunctional OER/ORR activity. The bifunctional index (ΔE) is substantially reduced with increasing of Sr contents and achieves an optimal value of 0.85 V for La1.4Sr0.6NiMnO6, exceeding that of widely studied LaNiO3. Our study on electronic structures reveals that the enhancement of the ORR and OER activities strongly correlates with the appearance of Ni3+ oxidation states and the upshift of the O 2p-band center promoted by Sr doping. Furthermore, an increase of hole states, derived from Ni3+ states, reduces the energy barrier for the electron transfer from 0.44 to 0.12 eV and hence improves the intrinsic OER activities. The tuning of the electronic structure that leads to higher OER and ORR activities in La2-xSrxNiMnO6 can be extended to other materials for the design of active bifunctional electrocatalysts. </p