Humanoid-OmniOcc delivers a large-scale panoramic stereo occupancy dataset for humanoid robots via Real2Sim2Real, with a model that outperforms monocular baselines in both unseen sim scenes and real settings.
Occ3d: A large-scale 3d occupancy prediction benchmark for autonomous driving
6 Pith papers cite this work. Polarity classification is still indexing.
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2026 6representative citing papers
Introduces PKL to rank planning-critical occluded agents, creates a VLM-annotated benchmark on nuScenes, and shows fine-tuning on this data improves performance ~30% over random selection with smaller models outperforming larger zero-shot counterparts.
Offline VLM instance audits, grounded to matched object voxels and distilled via taxonomy, attribute, and graph losses, raise OccWorld and GaussianWorld closed-set occupancy mIoU without inference-time VLM cost.
HiPR improves 3D occupancy prediction by reparameterizing image-to-voxel projections using LiDAR-derived height priors to adapt sampling ranges to scene sparsity and height variations.
GOLD-BEV learns dense BEV semantic maps including dynamic agents from ego-centric sensors by using synchronized aerial imagery for training supervision and pseudo-label generation.
InfiniVerse reconstructs 3D occupancy from one frame, extends scenes autoregressively, converts to video via diffusion, and uses re-projection feedback to achieve SOTA FID 6.4 and FVD 67.97 on Waymo and nuScenes.
citing papers explorer
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Humanoid-OmniOcc: Stereo-Based Full-View Occupancy Dataset for Embodied AI
Humanoid-OmniOcc delivers a large-scale panoramic stereo occupancy dataset for humanoid robots via Real2Sim2Real, with a model that outperforms monocular baselines in both unseen sim scenes and real settings.
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What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models
Introduces PKL to rank planning-critical occluded agents, creates a VLM-annotated benchmark on nuScenes, and shows fine-tuning on this data improves performance ~30% over random selection with smaller models outperforming larger zero-shot counterparts.
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VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models
Offline VLM instance audits, grounded to matched object voxels and distilled via taxonomy, attribute, and graph losses, raise OccWorld and GaussianWorld closed-set occupancy mIoU without inference-time VLM cost.
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Height-Guided Projection Reparameterization for Camera-LiDAR Occupancy
HiPR improves 3D occupancy prediction by reparameterizing image-to-voxel projections using LiDAR-derived height priors to adapt sampling ranges to scene sparsity and height variations.
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GOLD-BEV: GrOund and aeriaL Data for Dense Semantic BEV Mapping of Dynamic Scenes
GOLD-BEV learns dense BEV semantic maps including dynamic agents from ego-centric sensors by using synchronized aerial imagery for training supervision and pseudo-label generation.
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InfiniVerse: Occupancy Guided Unbounded Scene Generation for Autonomous Driving
InfiniVerse reconstructs 3D occupancy from one frame, extends scenes autoregressively, converts to video via diffusion, and uses re-projection feedback to achieve SOTA FID 6.4 and FVD 67.97 on Waymo and nuScenes.