#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
🌐📖Collective Licensing for AI Era: RSL Launches New Rights Model
Real Simple Licensing (RSL) has launched a nonprofit collective rights platform aimed at protecting online publishers and creators in the age of generative AI. Through the RSL Standard, the organization enables content owners to collectively negotiate fair compensation when their work is used to generate AI outputs, setting market-wide licensing terms.
Modeled after organizations like ASCAP and BMI in the music industry, the RSL Collective introduces a unified rights framework for the digital era. For the first time, publishers and creators can pool rights into a single platform to establish fair market prices and simplify licensing for AI companies, ensuring they are not left out of the AI economy.
#AIEthics#Copyright#RSL#GenerativeAI#ResponsibleAI
🎉 Нашу статью приняли на EMNLP 2025 в Main Track.
💪 Выводим распознавание жестовых языков на новый качественный уровень. В статье достигаем state-of-the-art🌿 на жестовых языках разных стран, включая в первую очередь русский жестовый язык (РЖЯ). Показываем, что качественный претрейн и предобработка — залог успеха.
Спасибо авторам: @your_petros@ilyaovodov@nagadit@hukenovs@karinakvanchiani
📝Жестовый язык: похожее в непохожем и наоборот
📖Logos as a Well-Tempered Pre-train for Sign Language Recognition
До встречи на конференции!
#research#rsl#emnlp