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Chandrakanth Gudavalli

2 accepted papers

2026

WRIVINDER: Towards Spatial Intelligence for Geo-locating Ground Images onto Satellite Imagery

CVPR 2026

Aligning ground-level imagery with geo-registered satellite maps is crucial for mapping, navigation, and situational awareness, yet remains challenging under large viewpoint gaps or when GPS is unreliable. We introduce Wrivinder, a zero-shot, geometry-driven framework that aggregates multiple ground

Cited by 0SourcecodeScholar
2024

WildlifeMapper: Aerial Image Analysis for Multi-Species Detection and Identification

CVPR 2024poster

We introduce WildlifeMapper (WM) a flexible model designed to detect locate and identify multiple species in aerial imagery. It addresses the limitations of traditional labor-intensive wildlife population assessments that are central to advancing environmental conservation efforts worldwide. While a…