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license: apache-2.0
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license: apache-2.0
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# Cross-Dataset Evaluation of Visual Semantic Segmentation Models for Off-Road Autonomous Driving
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#### *David Pascual-Hernández, Sergio Paniego, Roberto Calvo-Palomino, Inmaculada Mora-Jiménez, Jose María Cañas-Plaza*
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We provide weights for the models studied in *Cross-Dataset Evaluation of Visual Semantic Segmentation Models for Off-Road Autonomous Driving*. Directories nomenclature is defined as:
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```<dataset>-<ontology>-<data_augmentation>```
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- **Dataset**. Training dataset, either RELLIS-3D, GOOSE or a combination of both.
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- **Ontology**. Ontology used during training. It can either be the original dataset ontology or our unified coarser ontology.
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- **Data augmentation**. Data augmentation strategy, either *light* (used for inner-dataset experiments) or *strong* (used for cross-dataset experiments).
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All models have been fine-tuned using the pre-trained weights provided by [mmsegmentation](https://github.com/open-mmlab/mmsegmentation/tree/main) for the Cityscapes dataset.
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