1 citations · 1 across the 4 of their papers we have counts for
5 papers
HiddenObjects: Scalable Diffusion-Distilled Spatial Priors for Object Placement
Marco Schouten, Ioannis Siglidis, Serge Belongie +1
We propose a method to learn explicit, class-conditioned spatial priors for object placement in natural scenes by distilling the implicit placement knowledge encoded in text-condit…
An Interpretable Deep Learning Approach for Morphological Script Type Analysis
Malamatenia Vlachou-Efstathiou, Ioannis Siglidis, Dominique Stutzmann +1
Defining script types and establishing classification criteria for medieval handwriting is a central aspect of palaeographical analysis. However, existing typologies often encounte…
Diffusion Models as Data Mining Tools
Ioannis Siglidis, Aleksander Holynski, Alexei A. Efros +2
This paper demonstrates how to use generative models trained for image synthesis as tools for visual data mining. Our insight is that since contemporary generative models learn an…
OpenStreetView-5M: The Many Roads to Global Visual Geolocation
Guillaume Astruc, Nicolas Dufour, Ioannis Siglidis +10
Determining the location of an image anywhere on Earth is a complex visual task, which makes it particularly relevant for evaluating computer vision algorithms. Yet, the absence of…
The Learnable Typewriter: A Generative Approach to Text Analysis
Ioannis Siglidis, Nicolas Gonthier, Julien Gaubil +2
We present a generative document-specific approach to character analysis and recognition in text lines. Our main idea is to build on unsupervised multi-object segmentation methods…