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
arXiv:2607. 00417v1 Announce Type: cross Abstract: In the era of satellite constellations, multi-view optical satellite imagery is pivotal for Earth Observation (EO) and high-quality Digital Surface Model (DSM) reconstruction.
By Qiyan Luo, Yingdong Pi, Lekang Wen, Jie Yang, Xiaoyu Wang, Haiming Zhang, Mi Wang
The paper introduces GRF-Recon, a framework for stable and scalable feed-forward 3D reconstruction from long monocular image sequences. It combines coarse-to-fine trajectory alignment, lightweight geometric prior injection via LoRA adaptation, and a hybrid-weight sparse ray-field optimization to refine local point clouds while enforcing cross-frame consistency. An efficient trajectory stitching strategy with joint ray-error optimization further reduces accumulated drift, achieving competitive trajectory accuracy compared to SLAM systems while maintaining globally consistent reconstructions in large-scale scenarios.
By Enpeng Li, Yunzhou Zhang, Zhiyao Zhang, Dexuan Lyu, Chenyu Wang, Chiyuan Cui, Cheng Cheng
arXiv:2604.13183v4 Announce Type: replace
Abstract: Generalizable cross-view geo-localization aims to match the same location across views in unseen regions and conditions without GPS supervision. It...
By Hongyang Zhang, Yinhao Liu, Haitao Zhang, Zhongyi Wen, Zhenyu Kuang, Shuxian Liang, Xian-Sheng Hua
The paper introduces Epipolar Distillation (EpiDistill), a method that transfers scale‑aware geometric priors from multi‑view models to monocular depth foundation models using Rectified Stereo Tokens. By preserving epipolar attention patterns, the single‑view model maintains geometric consistency without needing multi‑view inputs during inference. Experiments show significant improvements in zero‑shot metric depth estimation on challenging datasets such as ETH3D and DIODE, and the approach consistently boosts performance of state‑of‑the‑art ViT‑based models like UniDepthV2 and DepthPro.
By Jung-Hee Kim, Xiaoming Liu
arXiv:2610.01098v1 Announce Type: new
Abstract: Illusory matches between distinct yet visually similar 3D surfaces--doppelgangers--remain a fundamental obstacle for large-scale, in-the-wild 3D recons...
By Hanyuan Xiao, Gonglin Chen, Haolin Xiong, Wenbin Teng, Haiwei Chen, Yajie Zhao