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XuyangBai / TransFusion

[PyTorch] Official implementation of CVPR2022 paper "TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers". https://arxiv.org/abs/2203.11496
Apache License 2.0
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Low mAP when training Transfusion with lidar_only on nuscenes v1.0-mini dataset #96

Open 2460707925 opened 1 year ago

2460707925 commented 1 year ago

I am trying to reproduce the results of the Transfusion model on the nuscenes v1.0-mini dataset using the lidar_only configuration (transfusion_nusc_pillar_L.py). However, after training for 20 epochs on a single 3090ti GPU, my mAP is only 0.1611, which is much lower than the reported mAP in the paper.

I have followed the instructions in the official Transfusion repository and used the latest version of the code. My dataset is the nuscenes v1.0-mini dataset, and I have not made any modifications to the code or the dataset. Here are the details of my setup:

Dataset: nuscenes v1.0-mini Configuration: transfusion_nusc_pillar_L.py Hardware: single 3090ti GPU I have also tried training the model for more epochs (up to 50 epochs), but the mAP does not seem to improve significantly.

Could someone please help me diagnose the issue or suggest possible solutions? Thank you!

Feel free to modify the issue text as needed, and provide more details if you think it would be helpful. Good luck with reproducing the Transfusion results!

2000lf commented 5 months ago

@2460707925 Could you tell me how to prepare the nuscenes v1.0-mini dataset

2460707925 commented 5 months ago

@2460707925 Could you tell me how to prepare the nuscenes v1.0-mini dataset

juse use mmdet3d create_dataset , set version== v1.0-mini

docckey commented 4 months ago

@2460707925 Could you tell me if you solved the problem of poor training results on the mini dataset.