HuMemSLAM: Efficient Human-Inspired Semantic Place Recognition for Robust Visual SLAM
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
The Flow has not summarised this story yet — read it at arXiv Computer Vision.
arXiv:2607.20116v2 Announce Type: replace Abstract: Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, diff...
DXPR is a depth‑based cross‑modal place recognition framework that matches monocular camera queries to a LiDAR map using a single vision foundation model backbone. By converting both modalities into a unified depth image representation, DXPR learns modality‑invariant global descriptors without modality‑specific encoders. A geometry‑aware overlap miner refines pairwise metric learning by computing pixel‑level overlap scores, and extensive tests on KITTI and Boreas show strong performance across seasons, weather, and day/night conditions, outperforming prior CMPR baselines.
GeoStore is a new benchmark for fine‑grained point‑of‑interest (POI) localization that matches close‑up storefront photos against large geo‑tagged street‑view images, a task distinct from traditional visual place recognition. The paper shows that global‑descriptor methods designed for symmetric matching perform poorly on this asymmetric problem, and introduces GLAM, a Global‑to‑Local Asymmetric Matching approach that combines a global retrieval anchor with a lightweight local re‑ranking using pooled region tokens. GLAM achieves higher Recall@1/5/10 and mAP than strong baselines while using far fewer re‑ranking features and significantly lower per‑pair matching cost.
arXiv:2606. 30576v1 Announce Type: cross Abstract: Cross-view object geo-localization (CVOGL) aims to locate a target object from a query view (e.
Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, acquisition-time and imaging-platform differences between UAV and reference imagery induce substantial cross-domain appearance and viewpoint shifts, challenging robust six-degree-of-freedom (6-DoF) pose estimation.
arXiv:2608.28891v1 Announce Type: new Abstract: Pixel-level cross-view geo-registration aims to align a query image (e.g., drone) to a geo-referenced satellite map so that every query pixel can be ma...