arXiv:2504.11063
UKDM: Underwater keypoint detection and matching using underwater image enhancement techniques
원문 초록
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.
함께 살펴볼 논문
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GKNet: Graph-based Keypoints Network for Monocular Pose Estimation of Non-cooperative Spacecraft
HVI-CIDNet+: Beyond Extreme Darkness for Low-Light Image Enhancement
MAC-Lookup: Multi-Axis Conditional Lookup Model for Underwater Image Enhancement
Learning to See in the Extremely Dark
RT-X Net: RGB-Thermal cross attention network for Low-Light Image Enhancement
URWKV: Unified RWKV Model with Multi-state Perspective for Low-light Image Restoration
토론
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