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Source channel @githubtrending · Post #15062 · Aug 15

#python#mllm#point_clouds#scene_understanding#spatial_intelligence SpatialLM is a powerful 3D language model that turns complex 3D point cloud data from videos, RGBD images, or LiDAR into clear, structured 3D scene layouts showing walls, doors, windows, and objects with labels. It works without needing special equipment and can detect user-specified object categories. This helps you understand and analyze indoor spaces better, useful for robotics, navigation, and 3D design. You can run it on your data, visualize results, and even customize detection tasks easily, making 3D scene understanding more accessible and flexible for many applications. https://github.com/manycore-research/SpatialLM

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DataSci NU

@nu_datasci · Post #3 · 02/18/2023, 01:21 PM

Attention all Data Science enthusiasts! We're thrilled to announce that our club is kicking off a series of exciting events that cover a wide range of topics in data analytics, computer vision, natural language processing, and machine learning in robotics. First up, we have a speech and Q&A session with Professor Ernazar Abdikamalov, a renowned researcher who uses machine learning in physics. Following that, we'll hear from experts in the industry, including representatives from Kolesa Group and Jusan Group. And to wrap up the series, we're hosting a sponsored hackathon on data analytics! This is a fantastic opportunity to expand your knowledge, network with industry professionals, and put your skills to the test. Stay tuned for more information on the dates and details of each event. Link to our Instagram We can't wait to see you there! #DataSci#DataAnalytics#ComputerVision#NLP#MLinRobotics💻🔬🤖