Abstract
The purpose of this paper is to explore the use of underwater image enhancement techniques to improve keypoint detection and matching. By applying advanced deep learning models, including generative adversarial networks and convolutional neural networks, we aim to find the best method which improves the accuracy of keypoint detection and the robustness of matching algorithms. We evaluate the performance of these techniques on various underwater datasets, demonstrating significant improvements over traditional methods.
Abstract (translated)
本文的目的是探讨使用水下图像增强技术来提升关键点检测和匹配的效果。通过应用包括生成对抗网络（GAN）和卷积神经网络（CNN）在内的先进深度学习模型，我们旨在找到能够提高关键点检测准确性及匹配算法鲁棒性的最佳方法。我们在多种水下数据集上评估了这些技术的性能，并展示了相对于传统方法有显著的进步。
URL
https://arxiv.org/abs/2504.11063
