3 papers
cs.CV2026
Depth-Guided Privacy-Preserving Visual Localization Using 3D Sphere Clouds
Heejoon Moon, Jongwoo Lee, Jeonggon Kim +1
The emergence of deep neural networks capable of revealing high-fidelity scene details from sparse 3D point clouds has raised significant privacy concerns in visual localization in…
cs.CV2026
Revisiting Geometric Obfuscation with Dual Convergent Lines for Privacy-Preserving Image Queries in Visual Localization
Jeonggon Kim, Heejoon Moon, Je Hyeong Hong
Privacy-Preserving Image Queries (PPIQ) are an emerging mechanism for cloud-based visual localization, enabling pose estimation from obfuscated features instead of private images o…
cs.CV2026
Shape-of-You: Fused Gromov-Wasserstein Optimal Transport for Semantic Correspondence in-the-Wild
Jiin Im, Sisung Liu, Je Hyeong Hong
Semantic correspondence is essential for handling diverse in-the-wild images lacking explicit correspondence annotations. While recent 2D foundation models offer powerful features,…