5 citations · 5 across the 1 of their papers we have counts for
3 papers
D2D: Keypoint Extraction with Describe to Detect Approach
Yurun Tian, Vassileios Balntas, Tony Ng +3
In this paper, we present a novel approach that exploits the information within the descriptor space to propose keypoint locations. Detect then describe, or detect and describe joi…
HDD-Net: Hybrid Detector Descriptor with Mutual Interactive Learning
Axel Barroso-Laguna, Yannick Verdie, Benjamin Busam +1
Local feature extraction remains an active research area due to the advances in fields such as SLAM, 3D reconstructions, or AR applications. The success in these applications relie…
Key.Net: Keypoint Detection by Handcrafted and Learned CNN Filters
Axel Barroso-Laguna, Edgar Riba, Daniel Ponsa +1
We introduce a novel approach for keypoint detection task that combines handcrafted and learned CNN filters within a shallow multi-scale architecture. Handcrafted filters provide a…