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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

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.CV2026

Beyond Flat Labels: Level-Restricted Contrastive Learning for Hierarchical Fine-Grained Vision Classification

Zhiyuan Tao, Srikumar Sastry, Matthew J Thompson +9

Multimodal contrastive learning has enabled zero-shot visual classification by aligning images with textual categories. However, in hierarchically structured label spaces, existing…

cs.CV2026

DiffVAS: Diffusion-Guided Visual Active Search in Partially Observable Environments

Anindya Sarkar, Srikumar Sastry, Aleksis Pirinen +2

Visual active search (VAS) has been introduced as a modeling framework that leverages visual cues to direct aerial (e.g., UAV-based) exploration and pinpoint areas of interest with…

cs.CV2026

Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping

Subash Khanal, Srikumar Sastry, Aayush Dhakal +3

We present Sat2Sound, a unified multimodal framework for geospatial soundscape understanding, designed to predict and map the distribution of sounds across the Earth's surface. Exi…

cs.CV2026

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…