6 citations · 9 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Prompt-Based Segmentation at Multiple Resolutions and Lighting Conditions using Segment Anything Model 2
Osher Rafaeli, Tal Svoray, Roni Blushtein-Livnon +1
This paper provides insights on the effectiveness of the zero shot, prompt-based Segment Anything Model (SAM) and its updated versions, SAM 2 and SAM 2.1, along with the non-prompt…