| --- |
| library_name: xcalib |
| tags: |
| - camera-lidar |
| - cross-modal-matching |
| - extrinsic-calibration |
| - jetson |
| - onnx |
| - tensorrt |
| pipeline_tag: keypoint-detection |
| --- |
| |
| # xcalib model weights |
|
|
| Trained checkpoints for the matching front-end studied in *Position Encoding in |
| Detection-Based LiDAR-Camera Matching: A Diagnostic Study at Infrastructure |
| Sites*. |
|
|
| <!-- public-only --> |
| This repo is public and accompanies the accepted xcalib paper. |
|
|
| ## Authors |
|
|
| Lihao Guo, Jiahao Tang, Tam Bang, Tianya Zhang, Austin Harris, Mina Sartipi, Siyang Cao |
|
|
| ## Usage |
|
|
| ```python |
| from xcalib import Matcher |
| |
| matcher = Matcher.from_pretrained("crlite", site="a9_dataset_r02_s01") |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{guo2026xcalib, |
| author = {Guo, Lihao and Tang, Jiahao and Bang, Tam and Zhang, Tianya and |
| Harris, Austin and Sartipi, Mina and Cao, Siyang}, |
| title = {Position Encoding in Detection-Based LiDAR--Camera Matching: |
| A Diagnostic Study at Infrastructure Sites}, |
| journal = {IEEE Sensors Letters}, |
| year = {2026}, |
| note = {Accepted. Paper URL pending. Code: |
| https://github.com/radar-lab/xcalib}, |
| } |
| ``` |
| <!-- /public-only --> |
|
|
| ## Documentation |
|
|
| Documentation (installation, API reference, input protocol, ONNX/TensorRT |
| export) is hosted at **https://radar-lab.github.io/xcalib**: |
|
|
| - [Home & quickstart](https://radar-lab.github.io/xcalib/) |
| - [Input protocol](https://radar-lab.github.io/xcalib/protocol/) |
| - [Models & datasets - loading from the Hub](https://radar-lab.github.io/xcalib/hub/) |
| - [API reference](https://radar-lab.github.io/xcalib/api/) |
|
|
| <!-- BEGIN generated files table --> |
| ## Files |
|
|
| | model | site | file | sha256 | |
| |---|---|---|---| |
| | `calibrefine` | `a9_dataset_r02_s01` | `checkpoints/calibrefine_a9_dataset_r02_s01_best.pth` | `768cce41b221c64136060e26c9573f04124c839a47397aef30de6a1e9152efe1` | |
| | `calibrefine` | `a9_dataset_r02_s01` | `configs/calibrefine_a9_dataset_r02_s01.yaml` | `8bccf8eaf479e5a238921c2b450a9990d8edab33ba08b645960379991e1a1feb` | |
| | `crlite` | `a9_dataset_r02_s01` | `checkpoints/crlite_a9_dataset_r02_s01_best.pth` | `16a07ed95befb632c67fe48ac3b62bdb342e21ec26072649b1acb556e0bd5dd8` | |
| | `crlite` | `a9_dataset_r02_s01` | `configs/crlite_a9_dataset_r02_s01.yaml` | `0a1cc325c6cc7925cb8304a4500accd68bfa0474b13e9f9f318dbb9f2281ff46` | |
| | `crlite_2dpe` | `a9_dataset_r02_s01` | `checkpoints/crlite_2dpe_a9_dataset_r02_s01_best.pth` | `c0c523d0fc945432fb9ef03132774bed2508ade91512c4a699b2d8201103a920` | |
| | `crlite_2dpe` | `a9_dataset_r02_s01` | `configs/crlite_2dpe_a9_dataset_r02_s01.yaml` | `b016e476b1a146ed8098bb9f957d9b88796005f55e328a15ac2b53b42d6ecd1d` | |
| | `crlite_vit_exp1` | `a9_dataset_r02_s01` | `checkpoints/crlite_vit_exp1_a9_dataset_r02_s01_best.pth` | `66d0cd7a7c1d88d8415da844798ea978d415c184409989b9a2f13a0061c57222` | |
| | `crlite_vit_exp1` | `a9_dataset_r02_s01` | `configs/crlite_vit_exp1_a9_dataset_r02_s01.yaml` | `12df9d18d3e977954ffd7aaa92be5bb29d5c7ee374a136c026b32362946492ce` | |
| | `crlite_vit_exp3` | `a9_dataset_r02_s01` | `checkpoints/crlite_vit_exp3_a9_dataset_r02_s01_best.pth` | `faa7cc851cb11ac748657edf4bfb03d9988d108e936c3ba46950ec734d48358d` | |
| | `crlite_vit_exp3` | `a9_dataset_r02_s01` | `configs/crlite_vit_exp3_a9_dataset_r02_s01.yaml` | `62d320c6f2451dd4669cacaf007013ab206c8f91680441aa7f37d4f065b57acf` | |
| <!-- END generated files table --> |
|
|
