Radarpillars Vod

--- license: apache-2.0 library_name: OpenPCDet pipeline_tag: object-detection tags: - 3d-object-detection - 4d-radar - radar-perception - autonomous-driving - pointpillars - openpcdet - view-of-delft datasets: - view-of-delft metrics: - mAP --- # RadarPillars — View-of-Delft (radar-only 3D object detection) Radar-only 3D object detection on the **View-of-Delft (VoD)** dataset — an OpenPCDet-based reproduction of **RadarPillars** ([Musiat et al., IROS 2024](https://arxiv.org/abs/2408.05020)). This checkpoint **reproduces and exceeds** the published result using 4D radar point clouds only (no camera, no LiDAR). - 📄 Paper: https://arxiv.org/abs/2408.05020 - 💻 Code, configs & full ablation: https://github.com/fthbng77/RadarPillar ## Results (mAP_3D, R11) | Method | Car @ 0.50 | Ped @ 0.25 | Cyc @ 0.25 | mAP_3D | |---|:---:|:---:|:---:|:---:| | **This checkpoint (best seed, s3)** | **41.58** | **44.78** | 71.31 | **52.56** | | 3-seed mean | 41.02 | 43.15 | 70.12 | 51.43 ± 0.99 | | RadarPillars (paper) | 41.10 | 38.60 | 72.60 | 50.70 | **+1.86 mAP_3D over the paper** (best seed). Checkpoint: seed s3 @ epoch 60 (eval-best). ## Usage ```bash git clone https://github.com/fthbng77/RadarPillar cd RadarPillar python setup.py develop # download this checkpoint huggingface-cli download fthbng77/radarpillars-vod radarpillar_vod_best_map52.56.pth --local-dir weights # evaluate python tools/test.py \ --cfg_file tools/cfgs/vod_models/vod_radarpillar_rot.yaml \ --ckpt weights/radarpillar_vod_best_map52.56.pth ``` ## Architecture PillarVFE (radial-velocity decomposition) → PillarAttention (masked self-attention) → PointPillarScatter → BaseBEVBackbone → AnchorHeadSingle (Car / Pedestrian / Cyclist). ~0.27M params. See the [GitHub repo](https://github.com/fthbng77/RadarPillar) for full details. ## Citation ```bibtex @inproceedings{radarpillars2024, title = {RadarPillars: Efficient Object Detection from 4D Radar Point Clouds}, author = {Musiat, Alexander and Reichardt, Laurenz and Schulze, Michael and Wasenm{\"u}ller, Oliver}, booktitle = {Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS)}, year = {2024} } ``` License: Apache-2.0. Built on [OpenPCDet](https://github.com/open-mmlab/OpenPCDet).