Official code for 'Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urban Driving Scenes'

Last update: Dec 29, 2022

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Overview

PEBAL

This repo contains the Pytorch implementation of our paper:

Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urban Driving Scenes

Yu Tian*, Yuyuan Liu*, Guansong Pang, Fengbei Liu, Yuanhong Chen, Gustavo Carneiro.

Inference

Checkpoint for anomaly segmentation

After downloading the pre-trained checkpoint, simply run the following command:

python test.py

Training Code will be released soon

Citation

If you find this repo useful for your research, please consider citing our paper:

@misc{tian2021pixelwise,
      title={Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes}, 
      author={Yu Tian and Yuyuan Liu and Guansong Pang and Fengbei Liu and Yuanhong Chen and Gustavo Carneiro},
      year={2021},
      eprint={2111.12264},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Owner

Yu Tian

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Official code for 'Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentationon Complex Urban Driving Scenes'

Related tags

Overview

PEBAL

Inference

Citation

Owner

Yu Tian

A full pipeline AutoML tool for tabular data

For the paper entitled ''A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining''

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