Towards Learning to Complete Anything in Lidar
Ayça Takmaz, Cristiano Saltori, Neehar Peri, Tim Meinhardt, Riccardo de Lutio, Laura Leal-Taixé, Aljosa Osep
2025年份
2顶会引用
摘要
Figure 1. Learning to Complete Anything in Lidar. Given a sparse Lidar point cloud, CAL (Complete Anything in Lidar) localizes, reconstructs, and, optionally, recognizes objects in a zero-shot fashion. By providing a semantic class vocabulary of specific object classes at test time, CAL can be prompted to perform Semantic Scene Completion (SSC), Panoptic Scene Completion (PSC), or (amodal) 3D Object Detection. Note that CAL only takes a single Lidar scan as input; RGB images are shown for visualization purposes only.
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