FreeOcc enables training-free open-vocabulary 3D occupancy prediction from RGB-D sequences by combining SLAM, dense Gaussian maps, off-the-shelf vision-language models, and probabilistic projection, achieving over 2x gains on benchmarks and zero-shot transfer to novel scenes.
Occnerf: Self- supervised multi-camera occupancy prediction with neural radiance fields.CoRR, abs/2312.09243
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A 3D Language-Embedded Gaussians framework with opacity-aware Poisson volumetric aggregation and progressive temperature decay achieves 59.50 IoU and 21.05 mIoU on Occ-ScanNet for open-vocabulary indoor occupancy.
BePo proposes a dual BEV and sparse-points representation with cross-attention fusion for more accurate and efficient 3D occupancy prediction on autonomous driving benchmarks.
citing papers explorer
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FreeOcc: Training-Free Embodied Open-Vocabulary Occupancy Prediction
FreeOcc enables training-free open-vocabulary 3D occupancy prediction from RGB-D sequences by combining SLAM, dense Gaussian maps, off-the-shelf vision-language models, and probabilistic projection, achieving over 2x gains on benchmarks and zero-shot transfer to novel scenes.
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Monocular Open Vocabulary Occupancy Prediction for Indoor Scenes
A 3D Language-Embedded Gaussians framework with opacity-aware Poisson volumetric aggregation and progressive temperature decay achieves 59.50 IoU and 21.05 mIoU on Occ-ScanNet for open-vocabulary indoor occupancy.
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BePo: Dual Representation for 3D Occupancy Prediction
BePo proposes a dual BEV and sparse-points representation with cross-attention fusion for more accurate and efficient 3D occupancy prediction on autonomous driving benchmarks.