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Owen-Liuyuxuan / visualDet3D

Official Repo for Ground-aware Monocular 3D Object Detection for Autonomous Driving / YOLOStereo3D: A Step Back to 2D for Efficient Stereo 3D Detection
https://owen-liuyuxuan.github.io/papers_reading_sharing.github.io/3dDetection/GroundAwareConvultion/
Apache License 2.0
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Clarification about multi-bin classification loss? #43

Open sauravshanu opened 2 years ago

sauravshanu commented 2 years ago

Hi,

Thanks for providing the code. I have a question about the multi-bin classification loss. In the Mono3D paper, it is mentioned that the cross-entropy loss is used for the multi-bin classification of width, height, and length.

However, looking at the code in detection_3d_head.py, I find that it is being used only for angle alpha. Am I understanding the code wrong? Can you please clarify that?

Thank you

Owen-Liuyuxuan commented 2 years ago

When I try to open-source the code, I made it easier to adapt to other datasets with more classes, so the multi-bin classification for rotation is skipped.