3 papers
cs.CV2026
GeoNLI - A Natural Language Interpreter for Satellite Imagery
Ashutosh Gandhe, Anupam Rawat, Geet Sethi +5
Multi-modal multitasking models have shown strong performance on remote sensing datasets. However, because these models are trained on heterogeneous data and vary across tasks, des…
cs.CV2026
Improving Visual Grounding in Remote Sensing via Cluster-Guided Refinement and Model Ensemble Voting
Panav Shah, Geet Sethi, Ashutosh Gandhe
Visual grounding aims to locate image regions that correspond to natural language descriptions and is a key component of interpretable vision systems. In remote sensing imagery, gr…
cs.CV2026
DiffuSAM: Diffusion Guided Zero-Shot Object Grounding for Remote Sensing Imagery
Geet Sethi, Panav Shah, Ashutosh Gandhe +1
Diffusion models have emerged as powerful tools for a wide range of vision tasks, including text-guided image generation and editing. In this work, we explore their potential for o…