Convolutional Scale Invariance for Semantic Segmentation
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README.md
compute_net_potentials.lua
data_container.lua
data_container_helper.lua
data_container_multifile.lua
data_container_multifile_threaded.lua
data_container_multifile_threaded_test.lua
data_container_multifile_threaded_val.lua
dataset_helper.lua
eval_helper.lua
evaluate_net.lua
load_cityscapes.lua
load_kitti.lua
plot_train_stats.lua
predict.lua
solver_config.lua
solver_config_cityscapes.lua
test.lua
train.lua
train_helper.lua

README.md

This is the code for the paper:

Convolutional Scale Invariance for Semantic Segmentation - GCPR 2016 (Oral)

We provide:

How to reproduce:

  1. Download KITTI or Cityscapes dataset
  2. Prepare the data for scale-invariant or single-scale model
  3. Modify all data paths for your system and run the training script:
th train.lua -model models/scale_invariant.lua -solver solver\_config.lua

If you find this code useful in your research, please cite:

@inproceedings{kreso16gcpr,
  title={Convolutional Scale Invariance for Semantic Segmentation},
  author={Krešo, Ivan and Čaušević, Denis and Krapac, Josip and Šegvić, Siniša},
  booktitle={German Conference on Pattern Recognition},
  year={2016},
  organization={Springer}
}