Abstract: Self-training is a novel learning paradigm that generates pseudolabels for unlabeled data, enabling deep learning models to be trained without the need for humanlabeled data. This article ...

Visual comparison between ESCNet and other SOTA methods. Our model accurately segments objects with complex backgrounds and intricate boundaries. For ease of use, we create a eval.sh script and a use ...

Abstract: In adverse environments, the detector often fails to detect degraded objects because they are almost invisible and their features are weakened by the environment. Common approaches involve ...