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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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The Digi Doodles

@Digi_doodles · Post #613 · 07/23/2025, 04:10 PM

InvisAbility — Snow Globe Projections in Hobart📖 July 2025 · Hobart Town Hall · Tasmania The Town Hall becomes a snow globe. 😇 As part of the InvisAbility project, this immersive installation uses light projections and interactive sound to tell stories of people with disabilities — in ways that are gentle, poetic, and public. It’s not just art — it’s presence made visible through tech. Created with community input and designed for everyone who’s ever felt unseen. Public space becomes a space of care, sound, and shimmering empathy☁️ #InvisAbility#PublicArt#ImmersiveArt#Accessibility#ArtAndTech