3 citations · 9 across the 22 of their papers we have counts for
7 papers · 2 filters
Chronosphere: Space-Time Tessellation of Local Climate Experts
Daniel Cher, Eric Xing, Kexing Li +3
We introduce Chronosphere, a spatio-temporal neural field that learns representations of climate. A central challenge in geographic representation learning is modeling environmenta…
Genesis: A Generative Engine for Hierarchical Satellite Image Synthesis
Subash Khanal, Yangzhi Cui, Daniel Cher +4
Earth observation is fundamentally multi-scale; geospatial tasks span varied resolutions, and satellite imagery is organized into cascading tile pyramids that nest fine detail with…
Trajectory-aware Cross-view Geo-localization with Sequential Observations
Tianyi Gao, Jiayu Lin, Danielle Beaulieu +1
Cross-view geo-localization matches ground-level observations against geo-tagged satellite imagery. Recent methods show that sequential queries such as video clips yield richer spa…
TerraDiT-: Unified Spatial Control for Satellite Image Synthesis with Any Geospatial Primitive
Brian Wei, Srikumar Sastry, Daniel Cher +2
Generative models have achieved remarkable progress, yet applying them to satellite imagery remains challenging. Unlike natural imagery, satellite scenes are structured by spatiall…
Tessellating The Earth
Daniel Cher, Hamza Iqbal, Eric Xing +2
Geolocation encoders, which map geographic coordinates to learned representations, are emerging as an effective means of capturing visual and non-visual characteristics from a lati…
PRUE: A Practical Recipe for Field Boundary Segmentation at Scale
Gedeon Muhawenayo, Caleb Robinson, Subash Khanal +10
Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field mapping are sensitive to illuminat…
SimLBR: Learning to Detect Fake Images by Learning to Detect Real Images
Aayush Dhakal, Subash Khanal, Srikumar Sastry +4
The rapid advancement of generative models has made the detection of AI-generated images a critical challenge for both research and society. Recent works have shown that most state…