Merge branch 'main' of https://github.com/OpenDriveLab/UniAD into main

README.md

@@ -48,7 +48,7 @@ https://github.com/OpenDriveLab/UniAD/assets/48089846/bcf685e4-2471-450e-8b77-e0
 
 - **`Paper Title Change`**: To avoid confusion with the "goal-point" navigation in Robotics, we change the title from "Goal-oriented" to "Planning-oriented" suggested by Reviewers. Thank you!
 
-- **`2023/06/12`** Bugfix [Ref: https://github.com/OpenDriveLab/UniAD/issues/21]: Previously, the performance of the stage1 model (track_map) could not be replicated when trained from scratch, due to mistakenly adding `loss_past_traj` and `freezing img_neck` and `BN`. By removing `loss_past_traj` and unfreezing `img_neck` and `BN` in training, the reported results could be reproduced (AMOTA: 0.393, [stage1_train_log](https://github.com/OpenDriveLab/UniAD/releases/download/v1.0/uniad_reproduce_stage1_gpu16_train.log)).
+- **`2023/06/12`** Bugfix [Ref: https://github.com/OpenDriveLab/UniAD/issues/21]: Previously, the performance of the stage1 model (track_map) could not be replicated when trained from scratch, due to mistakenly adding `loss_past_traj` and freezing `img_neck` and `BN`. By removing `loss_past_traj` and unfreezing `img_neck` and `BN` in training, the reported results could be reproduced (AMOTA: 0.393, [stage1_train_log](https://github.com/OpenDriveLab/UniAD/releases/download/v1.0/uniad_reproduce_stage1_gpu16_train.log)).
 
 - **`2023/04/18`** New feature: You can replace BEVFormer with other BEV Encoding methods, e.g., LSS, as long as you provide the `bev_embed` and `bev_pos` in [track_train](https://github.com/OpenDriveLab/UniAD/blob/cb4e3dc336ac9f94897ef3c7d85edba85a507726/projects/mmdet3d_plugin/uniad/detectors/uniad_track.py#L394) and [track_inference](https://github.com/OpenDriveLab/UniAD/blob/cb4e3dc336ac9f94897ef3c7d85edba85a507726/projects/mmdet3d_plugin/uniad/detectors/uniad_track.py#L661). Make sure your bevs and ours are of the same shape.
 - **`2023/04/18`** Base-model checkpoints are released.