---
tags:
- pytorch
- lidar
- 3d-object-detection
- test-time-adaptation
pipeline_tag: object-detection
---

# FIND Checkpoints

Source-pretrained SECOND-IoU checkpoints for **FIND: Frequency Invariance Disentanglement for Test-Time Adaptation in LiDAR 3D Detection** (NeurIPS 2026).

Paper: [arXiv:2611.09170](https://arxiv.org/abs/2611.09170)

| Checkpoint | Source dataset | Adaptation task |
| --- | --- | --- |
| [n2k.pth](checkpoints/n2k.pth) | nuScenes | nuScenes → KITTI |
| [w2k.pth](checkpoints/w2k.pth) | Waymo | Waymo → KITTI |
| [k2c.pth](checkpoints/k2c.pth) | KITTI | KITTI → KITTI-C |

Place the downloaded checkpoints in the `checkpoints/` directory of the [FIND codebase](https://github.com/llldx03/FIND).

Follow the [GitHub README](https://github.com/llldx03/FIND#readme) for installation, data preparation, source spectral statistics, and online adaptation.