| --- |
| license: apache-2.0 |
| tags: |
| - 3d-object-detection |
| - multi-object-tracking |
| - gaussian-splatting |
| - camera-radar-fusion |
| - nuscenes |
| datasets: |
| - nuscenes |
| --- |
| |
| # GaussianMOT |
|
|
| Joint 3D object detection and tracking on a camera–radar Gaussian BEV. |
| Code: <https://github.com/KimJunHan/GaussianMOT> |
|
|
| This repository holds the checkpoint reported in the paper (weights only, |
| end of the 24th training epoch). |
|
|
| | File | Size | SHA-256 | |
| |---|---|---| |
| | `gaussianmot_epoch23.ckpt` | 368 MB | `d3e3a5e55265b878420dbbcf1d6868e47350e8c968fb5061e2aad3b88af5dd23` | |
|
|
| ## Results (nuScenes val, inference seed 0) |
|
|
| | Detection | | Tracking | | |
| |---|---|---|---| |
| | mAP | 35.0 | AMOTA | 0.348 | |
| | NDS | 42.5 | AMOTP | 1.31 | |
| | mATE | 0.539 | Recall | 0.411 | |
| | mASE | 0.307 | ID-S | 897 | |
| | mAOE | 0.681 | | | |
| | mAVE | 0.511 | | | |
| | mAAE | 0.465 | | | |
|
|
| 6 cameras + 5 radars, 448×800 input, 6.5 FPS on an RTX 3090 (batch size 1). |
|
|
| ## Usage |
|
|
| ```bash |
| git clone https://github.com/KimJunHan/GaussianMOT && cd GaussianMOT |
| hf download kimjunhan/GaussianMOT gaussianmot_epoch23.ckpt --local-dir ckpt |
| python tools/evaluate.py checkpoint_path=ckpt/gaussianmot_epoch23.ckpt device=cuda |
| ``` |
|
|
| The file contains `state_dict` only (no optimizer state); it loads with |
| `tools/evaluate.py` as is. Densification draws random shifts at inference, so |
| results depend on `eval_seed` (default 0) in the last digit. |
|
|
