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Research questionHow can one 3D semantic occupancy model handle indoor and outdoor scenes with varying cameras, scales, and label taxonomies?Most 3D semantic occupancy models assume a fixed scene type and occupancy protocol, making them difficult to apply across indoor and outdoor environments. The challenge is to maintain consistent occupancy metrics while adapting the image-to-3D mapping to different cameras and scene scales.
Computer Vision
Image & Video Processing
Machine Learning
Latest papersRecent research connected to this question, newest first.OccAnyScene: Towards Unified Indoor-Outdoor 3D Occupancy PredictionThe source studies Cross-Scene 3D Semantic Occupancy Prediction and introduces OccAnyScene, a pixel-frustum-centered Gaussian framework built on a pretrained depth foundation model. Reported results cover the indoor Occ-ScanNet and outdoor SurroundOcc-nuScenes datasets; the input does not specify broader deployment conditions or access requirements.research paper · Sep 2, 2026
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