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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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UXLINK

@uxlink_community · Post #470 · 05/10/2025, 05:27 AM

最近の日本Web3界隈で目立つのが、UXLINKの存在感。🇯🇵🔍 CNPとの提携を皮切りに、日本ローカルの強力なIPとの協業が加速⚡ オンチェーン/オフチェーン両方でのコミュニティ展開に加え、 Web2企業とのクロスパートナー戦略も水面下で進行中🤝 “ユーザー起点のWeb3ソーシャル”という文脈で、 UXLINKは今、日本で一番面白い動きをしているかもしれない。🚀 #UXLINK#Web3JP#CNP#ソーシャルレイヤー#CommunityDriven One of the most quietly significant players gaining traction in Japan’s Web3 scene 🇯🇵👀#UXLINK Following its recent collaboration with CNP—a top domestic IP—UXLINK is making inroads across both native Web3 communities and mainstream Web2 circles 🤝 IRL activations, on-chain social dynamics, and a clear long-term strategy signal a serious Japan play 🎯 If you're tracking the rise of social infrastructure in Asia’s Web3 movement, this is one to watch. 📡 #UXLINK#Web3Japan#CommunityLayer#CNP#Web3Social