most citedSinkSAM-Net: Knowledge-Driven Self-Supervised Sinkhole Segmentation Using Topographic Priors and Segment Anything Model

5 citations · 5 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CV2026

Evaluating Semantic and Spatial Guidance for Foundation Model Segmentation of Small-Scale PV in Remote Sensing Imagery

Roni Blushtein-Livnon, Tal Svoray, Osher Rafaeli +4

Spatio-temporal PV data are essential for understanding adoption processes in off-grid regions, yet such data remain largely unavailable. Automated segmentation of remote sensing (…

econ.GN2026

From Expansion to Consolidation: Socio-Spatial Contagion Dynamics in Off-Grid PV Adoption

Roni Blushtein-Livnon, Tal Svoray, Itay Fischhendler +2

In traditional rural societies, where social ties are embedded in physical space, the diffusion of emerging technologies may be amplified through socio-spatial contagion (SSC). Suc…

cs.CV20265 cited

SinkSAM-Net: Knowledge-Driven Self-Supervised Sinkhole Segmentation Using Topographic Priors and Segment Anything Model

Osher Rafaeli, Tal Svoray, Ariel Nahlieli

Soil sinkholes significantly influence soil degradation, infrastructure vulnerability, and landscape evolution. However, their irregular shapes, combined with interference from sha…

cs.CV2026

On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentation

Roni Blushtein-Livnon, Osher Rafaeli, David Ioffe +3

Remote sensing (RS) image segmentation is constrained by the limited availability of annotated data and a gap between overhead imagery and natural images used to train foundational…

cs.CV2026

Test-Time Adaptation for Height Completion via Self-Supervised ViT Features and Monocular Foundation Models

Osher Rafaeli, Tal Svoray, Ariel Nahlieli

Accurate digital surface models (DSMs) are essential for many geospatial applications, including urban monitoring, environmental analyses, infrastructure management, and change det…

cs.CV2026

Seamless High-Resolution Terrain Reconstruction: A Prior-Based Vision Transformer Approach

Osher Rafaeli, Tal Svoray, Ariel Nahlieli

High-resolution elevation data is essential for hydrological modeling, hazard assessment, and environmental monitoring; however, globally consistent, fine-scale Digital Elevation M…