plain centerpoint-voxel(without better backbone like focalsparse conv,without better neck like SA-FPN,without better head like transfusionhead) + swin-tiny + fusion strategy.
News
(2022.9.4) rank 1st and 1st in the term of NDS and mAP on the nuScenes leaderboard among all methods that don't use TTA and Ensemble.
(2022.9.21) rank 1st and 2nd in the term of NDS and mAP on the nuScenes learderboard among all methods that use single model and TTA.
(2022.10.6) rank 1st and 3rd in the term of NDS and mAP on the nuScenes learderboard among all methods that use Ensemble. learderboard link
Hi, congratulate to YZLFusion getting great performance on nuScenes dataset.
I wonder that do you conduct cross-modal GT-Paste for YZLFusion? Or simply follows the fade strategy similar to TransFusion (so that no need for GT-Paste)? Besides, are you going to release a paper for YZLFusion?
Thanks!
Hi, Thanks for your awesome job!
I have some question about tta, 1) you use double flip or only horizontal direction flip? 2) In my configuration, the improvement from flip TTA is around 1 mAP, but nds don't have improvement, is that correct?thanks so much
Hi,
Thanks for the great work!
I find that YZLFusion improves NDS by ~2.0 when using the model ensemble strategy, which is a large improvement. I also tried to ensemble some models, including centerpoint, transfusion-L, and transfusion-LC. However, the performance is not good as expected (~0.5NDS improvement).
What models do you choose? Do you only use two models for the ensemble (1. larger backbone 2. models with TTA), as mentioned in the Nuscene Ensemble Model Performance Section? Does a single model with a larger backbone achieve better results than an normal size backbone?
Looking forward to your reply!