/ss4c

The implementation code of of the paper "Leveraging Semi-Supervised Learning for Domain Adaptation: Enhancing Safety at Construction Sites through Long-Tailed Object Detection".

Leveraging Semi-Supervised Learning for Domain Adaptation: Enhancing Safety at Construction Sites through Long-Tailed Object Detection

The implementation code of of the paper "Leveraging Semi-Supervised Learning for Domain Adaptation: Enhancing Safety at Construction Sites through Long-Tailed Object Detection". The full end-to-end code will be released after the paper is accepted.

Proposed Approach

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Installation

Clone MMDetection v2.18 and install the required packages: https://github.com/open-mmlab/mmdetection.git

Training and Testing

To train the model, run the following command: sh train_semi_ours.sh

To test the model and compare with baseline, run the following command: sh check_mAP.sh

Environment

The code is tested on the following environment:

  • Ubuntu 20.04
  • Python 3.8
  • GPU: NVIDIA GeForce RTX 4090