Domain

Unsupervised Domain Adaptation for Nighttime Aerial Tracking

Junjie Ye, Changhong Fu, Guangze Zheng, Danda Pani Paudel, and Guang Chen. Unsupervised Domain Adaptation for Nighttime Aerial Tracking. In CVPR, pages 1-10, 2022.

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Overview

UDAT is an unsupervised domain adaptation framework for visual object tracking. This repo contains its Python implementation.

Paper (coming soon) | NAT2021 benchmark

Testing UDAT

1. Preprocessing

Before training, we need to preprocess the unlabelled training data to generate training pairs.

  1. Download the proposed NAT2021-train set

  2. Customize the directory of the train set in lowlight_enhancement.py and enhance the nighttime sequences