poor performance about end-to-end-multi-view-fusion-for-3d-object-detection-in-lidar-point-clouds

[AndyYuan96]

first evaluate the model I provide, I don't know why you get the poor performance, maybe you should use the same setting.

[yytzsy]

first evaluate the model I provide, I don't know why you get the poor performance, maybe you should use the same setting.

I also got poor results if I trained the model from scratch with the default setting.

mvf_pp_dv:
Car [email protected], 0.70, 0.70:
bbox AP:0.0008, 0.0019, 0.0038
bev AP:62.8055, 54.6709, 54.6212
3d AP:0.0000, 0.0000, 0.0000
aos AP:0.00, 0.00, 0.00

mvf_paper_car:
Car [email protected], 0.70, 0.70:
bbox AP:0.0000, 0.0013, 0.0073
bev AP:55.4981, 49.7647, 49.4458
3d AP:0.0000, 0.0000, 0.0000
aos AP:0.00, 0.00, 0.00

But just testing with your provided pth file is OK --- the results are similar. I also wonder the possible reasons.

[wanghangege]

first evaluate the model I provide, I don't know why you get the poor performance, maybe you should use the same setting.

I also got poor results if I trained the model from scratch with the default setting.

mvf_pp_dv: Car [email protected], 0.70, 0.70: bbox AP:0.0008, 0.0019, 0.0038 bev AP:62.8055, 54.6709, 54.6212 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00

mvf_paper_car: Car [email protected], 0.70, 0.70: bbox AP:0.0000, 0.0013, 0.0073 bev AP:55.4981, 49.7647, 49.4458 3d AP:0.0000, 0.0000, 0.0000 aos AP:0.00, 0.00, 0.00

But just testing with your provided pth file is OK --- the results are similar. I also wonder the possible reasons.

I meet the same problem like yours, have you solved it ?