Release reported GaussianMOT checkpoint (epoch 23)

README.md

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+---
+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.

gaussianmot_epoch23.ckpt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d3e3a5e55265b878420dbbcf1d6868e47350e8c968fb5061e2aad3b88af5dd23
+size 367668342