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.
See through the dark: Learning illumination-affined representations for nighttime occupancy prediction
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2representative citing papers
SEPatch3D accelerates ViT-based 3D object detectors up to 57% faster than StreamPETR via dynamic patch sizing and cross-granularity enhancement while keeping comparable accuracy on nuScenes and Argoverse 2.
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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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Revisiting Token Compression for Accelerating ViT-based Sparse Multi-View 3D Object Detectors
SEPatch3D accelerates ViT-based 3D object detectors up to 57% faster than StreamPETR via dynamic patch sizing and cross-granularity enhancement while keeping comparable accuracy on nuScenes and Argoverse 2.