3 citations · 5 across the 5 of their papers we have counts for
5 papers
Noise-Response Calibration: A Causal Intervention Protocol for LLM-Judges
Maxim Khomiakov, Jes Frellsen
Large language models (LLMs) are increasingly used as automated judges and synthetic labelers, especially in low-label settings. Yet these systems are stochastic and often overconf…
GeoFormer: A Multi-Polygon Segmentation Transformer
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
In remote sensing there exists a common need for learning scale invariant shapes of objects like buildings. Prior works relies on tweaking multiple loss functions to convert segmen…
Polygonizer: An auto-regressive building delineator
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
In geospatial planning, it is often essential to represent objects in a vectorized format, as this format easily translates to downstream tasks such as web development, graphics, o…
Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery
Maxim Khomiakov, Alejandro Valverde Mahou, Alba Reinders Sánchez +2
We present a novel pipeline for learning the conditional distribution of a building roof mesh given pixels from an aerial image, under the assumption that roof geometry follows a s…
SolarDK: A high-resolution urban solar panel image classification and localization dataset
Maxim Khomiakov, Julius Holbech Radzikowski, Carl Anton Schmidt +4
The body of research on classification of solar panel arrays from aerial imagery is increasing, yet there are still not many public benchmark datasets. This paper introduces two no…