/CLSS_baseline

Continual Semantic Segmentation baseline (MiB, PLOP, DKD) It is based on DKD code implementation

Primary LanguagePythonGNU General Public License v3.0GPL-3.0

CLSS (Contiunal Learning Semantic Segmentation) baselines

  • This is CLSS baseline implementation
  • Currently, it includes MiB, PLOP, DKD.
  • The main implementation is based on dataset VOC2012 and ResNet-101 backbone.
  • ADE 20K dataset is not supported currently, but will be supported soon.

Environment

  • CUDA 11.1
  • python 3.8
  • The shell code for setting environment is in scripts/env_create.sh

training

  • The shell code for training is in ./z_exp_individual_cmd
    ./train_{dataset}_{scenarios}_{method}.sh
    For examples, ./train_voc_10-1_DKD.sh
    For MiB, PLOP which require 2 GPUs, please pass the argument GPU_NUMBER (ex 0,1) to .sh file
  • The configuration for each method is in 'configs/config_{dataset}_{method}.yaml'
  • The results are updated in wandb

configuration for each baseline

Pascal VOC 2012

coonfig MiB PLOP DKD STAR
epoch 30 30 60 60
lr 0.01 / 0.001 0.01 / 0.001 0.001/ 0.0001 0.001/ 0.0001
$\gamma$ (pos weight for BCE Loss) UnCE 1 2 / 1 4
Optimizer SGD (momentum 0.9, wd 1e-4, nesterov True) SGD (momentum 0.9, wd 1e-4) SGD (momentum 0.9) Adam (momentum 0.9)
$\alpha,\beta$ (hyperparameter for loss) 10 (lkd) 1 (pod) 5 / 5 (kd / dkd) 5 / 0.05 (pkd/cont)
batch size 24 24 32 24
lr Schedular PolyLR PolyLR PolyLR
GPUs RTX titian x 2 ? x 2 A5000 x 4 RTX 3090 x 2
augmentation same as [1]

ADE 20K

config MiB PLOP DKD STAR epoch 60 60 100 100 lr 0.01 / 0.001 0.01 / 0.001 0.0025 / 0.00025 0.00025 / 0.000025 $\gamma$ (pos weight for BCE Loss) UnCE 1 35 30 Optimizer SGD (momentum 0.9, wd 1e-4) SGD (momentum 0.9, wd 1e-4) SGD (momentum 0.9) Adam (momentum 0.9) $\alpha,\beta$ (hyperparameter for loss) 10 (lkd) 1 (pod) 5 / 5 (kd / dkd) 5 / 0.05 (pkd/cont) batch size 24 24 24 24 lr Schedular PolyLR PolyLR PolyLR + linear warm up GPUs RTX titian x 2 ? x 2 A5000 x 4 RTX 3090 x 2 augmentation same as [1]

Acknowledgements