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cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

TerraDiT: Point-Conditioned Diffusion Transformer for Satellite Image Synthesis

Srikumar Sastry, Dan Cher, Brian Wei +4

We introduce TerraDiT, a diffusion transformer designed for text-to-satellite image generation with point-based control. Existing controlled satellite image generative models often…

cs.CV2025

VectorSynth: Fine-Grained Satellite Image Synthesis with Structured Semantics

Daniel Cher, Brian Wei, Srikumar Sastry +1

We introduce VectorSynth, a diffusion-based framework for pixel-accurate satellite image synthesis conditioned on polygonal geographic annotations with semantic attributes. Unlike…