Georeferenced 3D reconstruction from ground images requires recovering not only the local scene geometry, but also localizing every camera center and 3D point in a geographic coordinate frame. Existin...
arXiv:2602.14929v2 Announce Type: replace
Abstract: Aligning ground-level imagery with geo-registered satellite maps is crucial for mapping, navigation, and situational awareness, yet remains challen...
By Chandrakanth Gudavalli, Tajuddin Manhar Mohammed, Abhay Yadav, Ananth Vishnu Bhaskar, Hardik Prajapati, Cheng Peng, Rama Chellappa, Shivkumar Chandrasekaran, B. S. Manjunath
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...
By Qingyang Liu, David G Shatwell, Parth Parag Kulkarni, Mubarak Shah
arXiv:2608.29211v1 Announce Type: new
Abstract: Ground image localization with respect to satellite imagery is a key enabler for metrically-accurate, geo-localized 3D scene reconstruction from uncons...
By Angel Daruna, Ben Southall, Niluthpol Chowdhury Mithun, Kshitij Minhas, Nicholas Meegan, Qiao Wang, Bogdan Matei, Supun Samarasekera, Rakesh Kumar
The paper proposes a new sequence-to-sequence formulation for multi-view stereo (MVS) that jointly predicts 3D geometry for all input views using a global transformer architecture. It introduces ray‑map embeddings to inject camera parameters into image tokens and a unified global cost volume to capture 3D structure across all views. Experiments on public benchmarks demonstrate state‑of‑the‑art performance, outperforming both traditional MVS and feed‑forward reconstruction baselines.
By Aoxiang Fan, Corentin Dumery, Nicolas Talabot, Pascal Fua
arXiv:2606. 30576v1 Announce Type: cross Abstract: Cross-view object geo-localization (CVOGL) aims to locate a target object from a query view (e.
By Liyao Wang, Ruipu Wu, Haojun Xu, Lei Shi, Linjiang Huang, Si Liu