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Source channel @githubtrending · Post #14934 · Jul 9

#python#3d_reconstruction#3d_vision#monocular_depth_estimation#monocular_geometry_estimation MoGe-2 is a powerful tool for estimating 3D geometry from single images. It can create detailed point maps, depth maps, and normal maps with high precision. This model is especially useful because it can predict geometry in metric scale, meaning it provides accurate measurements. It also enhances visual sharpness, making it better than previous versions. Users benefit from MoGe-2 by getting precise 3D information from just one photo, which is helpful for applications like robotics or video games. It's fast and works well with different image sizes. https://github.com/microsoft/MoGe

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Новая работа регулярного выпуска👇 🟢 2022 🟢 V. 9 🟢 Issue 4 🟢 No. 20229415🟢 Letter 📜 Local structure and ionic transport in acceptor-doped layered perovskite BaLa2In2O7 👩‍🎓 Nataliia A. Tarasova (https://orcid.org/0000-0001-7800-0172) 🏛 Institute of High Temperature Electrochemistry UB RAS, http://www.ihte.uran.ru 📚#layered_perovskite#ionic#conductivity#acceptor_doping#BaLa2In2O7 🔗https://doi.org/10.15826/chimtech.2022.9.4.15 https://journals.urfu.ru/index.php/chimtech/article/view/6272

Новая работа регулярного выпуска👇 🟢 2022 🟢 V. 9 🟢 Issue 4 🟢 No. 20229405🟢 📜 Phosphorus-doped protonic conductors based on BaLanInnO3n+1 (n = 1, 2): applying oxyanion doping strategy to the layered perovskite structure 👩‍🎓👨‍🎓 N. Tarasova (https://orcid.org/0000-0001-7800-0172), A. Galisheva (https://orcid.org/0000-0003-4346-5644) 🏛 Institute of High Temperature Electrochemistry, http://www.ihte.uran.ru 📚#layered#perovskite#oxyanion#doping#proton#conductivity#BaLaInO4#BaLa2In2O7 🔗https://doi.org/10.15826/chimtech.2022.9.4.05 https://journals.urfu.ru/index.php/chimtech/article/view/5979