Tutorial: A Hands-On Introduction to Benchmarking Neural Compression and Representation Learning for Earth Observation

Authors: Dávid Kerekes, Funxun Yu, Konstantin Klemmer, Conrad Albrecht
Cited by: 0

Abstract

This tutorial provides an introduction and hands-on session to NeuCo-Bench, https://github.com/embed2scale/NeuCo-Bench/tree/main , a benchmark framework that spun from the 2025 CVPR EARTHVISION workshop, https://www.grss-ieee.org/events/earthvision-2025/?tab=challenge . We designed NeuCo-Bench as an extendable, community-driven framework to evaluate neural compression and representation learning methods in the context of Earth Observation (EO) without the need for heavy compute resources. The growing volume and complexity of EO data calls for standardized, scalable, and reproducible tools that can assess the quality and utility of learned representations across diverse downstream tasks. NeuCo-Bench and its associated Earth2Vec community (https://earth2vec.github.io) that grew out of the Horizon Europe project Embed2Scale (https://embed2scale.eu) address this gap by offering a modular evaluation pipeline built around fixed-size, task-agnostic embeddings, enabling researchers and practitioners to consistently compare neural compression methods.

Fields of Study & Subjects

Advanced Data Compression Techniques Remote-Sensing Image Classification Advanced Neural Network Applications

Publication details

Journal / source
elib (German Aerospace Center)
Publication date
1 January 2026