Paolo Fraccaro — accepted AI-conference papers

2025

EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues

Sagar Soni, Akshay Dudhane, Hiyam Debary, Mustansar Fiaz, Muhammad Akhtar Munir, Muhammad Sohail Danish +5

CVPR 2025poster

Automated analysis of vast Earth observation data via interactive Vision-Language Models (VLMs) can unlock new opportunities for environmental monitoring, disaster response, and resource management. Existing generic VLMs do not perform well on Remote Sensing data, while the recent Geo-spatial VLMs r…

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2025

GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks

Muhammad Danish, Muhammad Akhtar Munir, Syed Roshaan Ali Shah, Kartik Kuckreja, Fahad Shahbaz Khan, Paolo Fraccaro +2

ICCV 2025poster

While numerous recent benchmarks focus on evaluating generic Vision-Language Models (VLMs), they do not effectively address the specific challenges of geospatial applications.Generic VLM benchmarks are not designed to handle the complexities of geospatial data, an essential component for application…

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2025

TerraMind: Large-Scale Generative Multimodality for Earth Observation

Johannes Jakubik, Felix Yang, Benedikt Blumenstiel, Erik Scheurer, Rocco Sedona, Stefano Maurogiovanni +10

ICCV 2025poster

We present TerraMind, the first any-to-any generative, multi-modal foundation model for Earth observation (EO). Unlike other multimodal models, TerraMind is pretrained on dual-scale representations combining both token-level and pixel-level data across modalities. On a token level, TerraMind encodes…

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2022

Deep Temporal Interpolation of Radar-Based Precipitation

Michiaki Tatsubori, Takao Moriyama, Tatsuya Ishikawa, Paolo Fraccaro, Anne Jones, Blair Edwards +2

ICASSP 2022accepted

When providing the boundary conditions for hydrological flood models and estimating the associated risk, interpolating precipitation at very high temporal resolutions (e.g. 5 minutes) is essential not to miss the cause of flooding in local regions. In this paper, we study optical flow-based interpol…

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