Skip to content

Training own LiDAR model gives significant increase in IOU compared to the paper #55

@seamie6

Description

@seamie6

After training my own LiDAR model, I get an IOU score of 63.8. This is quite a bit higher than the IOU presented in the paper, 60.8. Perhaps it is a typo in the paper??
I used the same parameters as the camera+radar model:

   --exp_name="rgb_mine" \
   --dset='trainval' \
   --data_dir=XYZ \
   --device_ids=[0,1,2,3] \
   --ncams=6 \
   --batch_size=8 \
   --grad_acc=5 \
   --res_scale=2 \
   --do_rgbcompress=True \
   --max_iters=25000 \
   --log_freq=100 \
   --val_freq=100 \
   --save_freq=5000 \
   --nworkers=12 \
   --nsweeps=5 \
   --use_radar=False \
   --use_metaradar=False \
   --use_radar_filters=False \
   --use_lidar=True \

I am currently training the camera+radar model to see what happens there, again using the same parameters.

Metadata

Metadata

Assignees

No one assigned

    Labels

    No labels
    No labels

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions