works on

From the 1 of 10 linked papers with an AI index.

activity
20242026
collaborators

10 papers

cs.CV2026

Robust RPC Bundle Adjustment for Multi-Date Satellite Imagery with Season-Invariant Correspondences

Roger Marí, Elías Masquil, Xavier Bou +2

The paper introduces a method that refines satellite camera models by using learned, season‑invariant feature matching and global image descriptors to select reliable image pairs,…

cs.CV2026

EOGS++: Earth Observation Gaussian Splatting with Internal Camera Refinement and Direct Panchromatic Rendering

Pierrick Bournez, Luca Savant Aira, Thibaud Ehret +1

Recently, 3D Gaussian Splatting has been introduced as a compelling alternative to NeRF for Earth observation, offering competitive reconstruction quality with significantly reduce…

cs.CV2026

Deep S2P: Integrating Learning Based Stereo Matching Into the Satellite Stereo Pipeline

Elías Masquil, Thibaud Ehret, Pablo Musé +1

Digital Surface Model generation from satellite imagery is a core task in Earth observation and is commonly addressed using classical stereoscopic matching algorithms in satellite…

cs.CV2026

An Industrial Dataset for Scene Acquisitions and Functional Schematics Alignment

Flavien Armangeon, Thibaud Ehret, Enric Meinhardt-Llopis +4

Aligning functional schematics with 2D and 3D scene acquisitions is crucial for building digital twins, especially for old industrial facilities that lack native digital models. Cu…

cs.CV2026

Diachronic Stereo Matching for Multi-Date Satellite Imagery

Elías Masquil, Luca Savant Aira, Roger Marí +3

Recent advances in image-based satellite 3D reconstruction have progressed along two complementary directions. On one hand, multi-date approaches using NeRF or Gaussian-splatting j…

cs.CV2026

Remote Sensing Change Detection via Weak Temporal Supervision

Xavier Bou, Elliot Vincent, Gabriele Facciolo +3

Semantic change detection in remote sensing aims to identify land cover changes between bi-temporal image pairs. Progress in this area has been limited by the scarcity of annotated…