--- license: other tags: - heal - horizon - bev --- # BevFormer+HENet Multitask The BevFormer+HENet multitask model uses HENet as the camera backbone to extract multi-view features, then BevFormer ViewTransformer and temporal BEV Encoder to transform them into bird's-eye-view features. BEV features are fed to both a detection head (3D object detection) and an occupancy head (FlashOcc-style semantic occupancy prediction), enabling joint det+occ training. --- ## Deployment Metrics ### Model Parameters | Model | Model Input | Backbone | Neck | Model Output | |---|---|---|---|---| | BevFusion | 6-camera multi-view image sequence `(B,6,3,512,960)` | HENet | FPN | det bounding boxes `(B,N,cls+reg)`; occ occupancy grid `(B,C,H,W)` | ### Accuracy Metrics | March | Metric | float | | --- | --- | --- | | J6M | NDS | 0.3573 | | | mAP | 0.3017 | | | Occ mIoU | 0.3146 | > Results measured with `march = March.NASH_M` (J6M) configuration. > > HEAL version: heal 0.0.2 / hbdk4-compiler 4.11.11 / horizon_plugin_pytorch 3.3.10. --- ## Model Overview ### Core Design The BevFormer+HENet multitask model uses HENet as the camera backbone to extract multi-view features, then BevFormer ViewTransformer and temporal BEV Encoder to transform them into bird's-eye-view features. BEV features are fed to both a detection head (3D object detection) and an occupancy head (FlashOcc-style semantic occupancy prediction), enabling joint det+occ training. - **Task type**: Multitask fusion (3D object detection + occupancy grid prediction). - **backbone**: HENet (camera feature extraction), extracting multi-view features. - **neck**: FPN. - **Detection head**: BevFormer detection head, outputting 10-class 3D bounding boxes + velocity (`num_classes=10`). - **Occupancy head**: Semantic occupancy prediction, 18 classes (`num_classes_occ=18`). - **BEV range**: `bev_size=(51.2, 51.2, 0.8)`, `bev_size_occ=(40, 40)`. - **Model input**: 6-camera image sequence `(B,6,3,512,960)` (`queue_length=1`). - **Model output**: det 3D bounding boxes + occ occupancy grid semantics `(B,C,H,W)`. ### Official Repo and Paper Official repo: https://github.com/fundamentalvision/BevFormer Paper: https://arxiv.org/abs/2203.17270 Note: The camera backbone HENet is a HEAL in-house implementation; the official repo uses a different backbone.