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SpatialLM, a new large language model designed for spatial understanding, has been released on Hugging Face. This model is capable of processing 3D point cloud data and generating structured outputs for 3D scene understanding. It can handle data from various sources, including monocular video sequences, RGBD images, and LiDAR sensors. The model is expected to enhance applications in robotics, augmented reality (AR), and virtual reality (VR). SpatialLM can quickly create accurate 3D designs and floor plans from basic video inputs and is based on two models utilizing Llama and Qwen architectures. The launch of SpatialLM opens new possibilities for AI-driven 3D reconstruction and real-world spatial intelligence.
SpatialLM is amazing. This AI quickly creates accurate 3D designs and floor plans from basic videos. You can find out how it works and how to use it. https://t.co/rklWLjN5om
SpatialLM is very interesting it's a new model that encodes text prompts (e.g. detect windows) and point clouds projected to an LLM 🤯 the LLM outputs 3D bounding boxes, very simple yet effective approach two models based on Llama and Qwen-0.5B and Llama-1B on @huggingface https://t.co/SHmMpMzPWY
SpatialLM Just Dropped on Hugging Face! A Large Language Model for Spatial Understanding, turning point cloud data into structured 3D scenes—perfect for robotics, AR/VR & more! #AI #SpatialLM #HuggingFace #3DAI https://t.co/EmvTX4beou
