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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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@googlefactss · Post #40365 · 12/19/2025, 09:21 PM

When the chat reaches 4,000 members or the channel 90,000, 10 group members will be allowed to create a post each, about a sfw topic of their own chosing. You must give @googlefactss permission to use your post and add it to the channel, with or without your username. More details will come after we hit these numbers. Invite friends, family, and coworkers to join. Do not spam/send links without permission of the place you send them in!! Our group links are: Main channel https://t.me/googlefactss Group: https://t.me/googlefactssgroup @googlefactss📢👥 #Community#Permission#Posts#Growth#KeepTrackOfThisPost