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EFFOcc

EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy Network

Demo videos

We provide lidar-camera occupancy prediction video of Occ3D-nuScenes dataset.

https://github.com/synsin0/EFFOcc/assets/37300008/6ab8238f-1d7f-4e4b-b4de-daff6a99ba41

Abstract(TL DR)

EFFOcc explores towards the minimal (minimal computation costs and minimal label costs) baseline for fast and high-performance 3D occupancy prediction with lidar-camera fusion. We show with proper detection pretraining, lightweight BEV-based fusion occnet can perform as well as voxel-based fusion occnets. Then, We conduct activate learning with maximum entropy on frame- and voxel-level to see the minimum label requirements for occupancy prediction.

Main Results

EFFOcc on Occ3D-nuScenes dataset: teaser EFFOcc on Occ3D-Waymo dataset: teaser EFFOcc on OpenOccupancy-nuScenes dataset: teaser

EFFOcc on two-stage active learning setting: teaser

Acknowledgements

Thanks to prior excellent open source projects: