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hustvl / osp

[ECCV 2024] Occupancy as Set of Points
MIT License
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Config and code modification for BEVFormer w/OSP #2

Open DengpanFu opened 1 month ago

DengpanFu commented 1 month ago

Hi, Thanks for your good job! I am trying to reproduce the result(mIoU=41.21) of BEVFormer w/OSP, but can not find the correct config. In your README-Results, OSP and BEVFormer w/OSP share the same config(projects/configs/osp.py), could you please provide the detailed config for BEVFormer w/OSP(e.g., the config to freeze trained BEVFormer)? Besides, I have some other questions:

  1. why self-attn osp.py is not needed in OSP?
  2. there are 3 encoder layers, but each layer forward twice BEVFormerEncoder, why? Any explanation is appreciated.
  3. i find a hard-code use_bev_volume=False, is this should be True for using OSP as a plugin to argument volume-based methods? and how to modify the code?

Looking forward to your reply, Thanks!

shawnsya commented 1 month ago

Hi! The config for BEVFormer can refer to the baseline provided by the CVPR2023 Challenge.

  1. The input query only interacts with the images and does not require self-attention.
  2. This part can refer to the oversample and GPCA mentioned in the paper.
  3. Thank you for pointing that out. This hard-code was added in a previous experiment and will be removed.