3 accepted papers
Local feature detection and description serve as the foundation for many 3D vision tasks. However, most existing algorithms rely on sharp images, resulting in degraded performance when motion blur occurs due to long exposure. To tackle this challenge, we propose an effective end-to-end model that jo…
Entity Alignment (EA) aims to find equivalent entity pairs between KGs, which is the core step to bridging and integrating multi-source KGs. In this paper, we argue that existing complex EA methods inevitably inherit the inborn defects from their neural network lineage: poor interpretability and wea…
Cross-lingual entity alignment (EA) aims to find the equivalent entities between crosslingual KGs (Knowledge Graphs), which is a crucial step for integrating KGs. Recently, many GNN-based EA methods are proposed and show decent performance improvements on several public datasets. However, existing G…