assets.md
May 5, 2023 ยท View on GitHub
Note that the mIoU is silighter higher than those in our paper (see logs for more details). Bellow are several changes in the training phase:
- We use SyncBN instead of BN/GN, which enhances the mIoU by ~0.3.
- The total training epoch is 15 instead of 24, which significantly reduces the training time.
- The models are trained with annotation-v0.1 (with less occupancy artifacts).
| Subset | Checkpoint | Logs | Note |
|---|---|---|---|
| Camera-based baseline | link (code:tlif) | link (code:ahqs) | train on 8 RTX3090 |
| LiDAR-based baseline | link (code:qdsl) | link (code:p3ra) | train on 8 RTX3090 |
| Multimodal baseline | link (code:d3vl) | link (code:f5qq) | train on 8 RTX3090 |
| Camera-based CONet | link (code:630w) | link (code:jb9o) | train on 8 A100 |
| LiDAR-based CONet | link (code:hnaf) | link (code:hqto) | train on 8 RTX3090 |
| Multimodal CONet | link (code:k9p9) | link (code:t7c5) | train on 8 A100 |
Google Drive link