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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.
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## 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.
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## 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.
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