BSI-MVS: multi-view stereo network with bidirectional semantic information.

The basic principle of multi-view stereo (MVS) is to perform 3D reconstruction by extracting depth information from multiple views. Most current SOTA MVS networks are based on Vision Transformer, which usually means expensive computational complexity. To reduce computational complexity and improve depth map accuracy, we propose a MVS network with Bidirectional Semantic Information (BSI-MVS). Firstly, we design a Multi-Level Spatial Pyramid module to generate multiple layers of feature map for extracting multi-scale information. Then we propose a 2D Bidirectional-LSTM module to capture bidirectional semantic information at different time steps in the horizontal and vertical directions, which contains abundant depth information. Finally, cost volumes are built based on various levels of feature maps to optimize the final depth map. We experiment on the DTU and BlendedMVS datasets. The result shows that our network, in terms of overall metrics, surpasses TransMVSNet, CasMVSNet, CVP-MVSNet, and AACVP-MVSNet respectively by 17.84%, 36.42%, 14.96%, and 4.86%, which also shows a noticeable performance enhancement in objective metrics and visualizations.

Construction of PdSe2/ZnIn2S4 heterojunctions with covalent interface for highly efficient photocatalytic hydrogen evolution.

Constructing semiconductor heterojunctions can enable novel schemes for highly efficient photocatalytic activity. However, introducing strong covalent bonding at the interface remains an open challenge. Herein, ZnIn2S4 (ZIS) with abundant sulfur vacancies (Sv) is synthesized with the presence of PdSe2 as an additional precursor. The sulfur vacancies of Sv-ZIS are filled by Se atoms of PdSe2, leading to the Zn-In-Se-Pd compound interface. Our density functional theory (DFT) calculations reveal the increased density of states at the interface, which will increase the local carrier concentration. Moreover, the length of the Se-H bond is longer than that of the SH bond, which is good for the evolution of H2 from the interface. In addition, the charge redistribution at the interface results in a built-in field, providing the driving force for efficient separation of photogenerated electron-hole. Therefore, the PdSe2/Sv-ZIS heterojunction with strong covalent interface exhibits an excellent photocatalytic hydrogen evolution performance (4423 µmol g-1h-1) with an apparent quantum efficiency (λ > 420 nm) of 9.1 %. This work will provide new inspirations to improve photocatalytic activity by engineering the interfaces of semiconductor heterojunctions.

MVS-T: A Coarse-to-Fine Multi-View Stereo Network with Transformer for Low-Resolution Images 3D Reconstruction.

A coarse-to-fine multi-view stereo network with Transformer (MVS-T) is proposed to solve the problems of sparse point clouds and low accuracy in reconstructing 3D scenes from low-resolution multi-view images. The network uses a coarse-to-fine strategy to estimate the depth of the image progressively and reconstruct the 3D point cloud. First, pyramids of image features are constructed to transfer the semantic and spatial information among features at different scales. Then, the Transformer module is employed to aggregate the image's global context information and capture the internal correlation of the feature map. Finally, the image depth is inferred by constructing a cost volume and iterating through the various stages. For 3D reconstruction of low-resolution images, experiment results show that the 3D point cloud obtained by the network is more accurate and complete, which outperforms other advanced algorithms in terms of objective metrics and subjective visualization.

V2T-GAN: Three-Level Refined Light-Weight GAN with Cascaded Guidance for Visible-to-Thermal Translation.

Infrared image simulation is challenging because it is complex to model. To estimate the corresponding infrared image directly from the visible light image, we propose a three-level refined light-weight generative adversarial network with cascaded guidance (V2T-GAN), which can improve the accuracy of the infrared simulation image. V2T-GAN is guided by cascading auxiliary tasks and auxiliary information: the first-level adversarial network uses semantic segmentation as an auxiliary task, focusing on the structural information of the infrared image; the second-level adversarial network uses the grayscale inverted visible image as the auxiliary task to supplement the texture details of the infrared image; the third-level network obtains a sharp and accurate edge by adding auxiliary information of the edge image and a displacement network. Experiments on the public dataset Multispectral Pedestrian Dataset demonstrate that the structure and texture features of the infrared simulation image obtained by V2T-GAN are correct, and outperform the state-of-the-art methods in objective metrics and subjective visualization effects.

Construction of 2D-layered quantum dots/2D-nanosheets heterostructures with compact interfaces for highly efficient photocatalytic hydrogen evolution.

The emergence of two dimensional (2D) nanosheets provides flexible platforms for the construction of semiconductor heterostructures for photocatalytic hydrogen evolution. However, the compact and conformal contact between the components with different dimensions remains challenge. Herein, we anchor the 2D layered black phosphorous quantum dots (BPQDs) onto the 2D ZnIn2S4 nanosheets with sulfur vacancies (V-ZIS). This unique interface between 2D layered QDs and 2D nanosheets ensures a sufficient contact area between the BPQDs and the V-ZIS, which is conducive to the transport and the spatial separation of photogenerated electrons and holes. A synergistic effect of sulfur vacancies and type-Ⅱ heterojunction results in an excellent photocatalytic hydrogen evolution performance of the BPQDs/V-ZIS composites. The hydrogen evolution rate by the BPQDs/V-ZIS without any noble-metal as cocatalyst is up to 5079 µmol g-1h-1 under visible light irradiation with an apparent quantum yield (AQY) of 12.03% at 420 nm, which is dramatically higher than most other photocatalysts reported previously.