activity
20172026
most citedDeep Generalized Max Pooling

96 citations · 265 across the 23 of their papers we have counts for

collaborators

26 papers

cs.CV2026

Handwriting Extraction and Analysis of Signature Lists in Swiss Popular Initiatives

Marco Peer, Thomas Gorges, Mathias Seuret +2

Popular initiatives and referendums are central to Swiss democracy, yet the validation of handwritten signature lists remains a labor-intensive manual process. This paper investiga…

cs.CV2026

ICDAR 2026 Competition on Writer Identification and Pen Classification from Hand-Drawn Circles

Thomas Gorges, Janne van der Loop, Lukas Hüttner +4

This paper presents CircleID, a large-scale ICDAR 2026 competition on writer identification and pen classification from scanned hand-drawn circles. The primary objective is to inve…

cs.CV2026

DRetHTR: Linear-Time Decoder-Only Retentive Network for Handwritten Text Recognition

Changhun Kim, Martin Mayr, Thomas Gorges +4

State-of-the-art handwritten text recognition (HTR) systems commonly use Transformers, whose growing key-value (KV) cache makes decoding slow and memory-intensive. We introduce DRe…

cs.CV2024★ 8 cited

Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models

Martin Mayr, Marcel Dreier, Florian Kordon +5

The imitation of cursive handwriting is mainly limited to generating handwritten words or lines. Multiple synthetic outputs must be stitched together to create paragraphs or whole…

cs.CV2024★ 6 cited

A Fair Evaluation of Various Deep Learning-Based Document Image Binarization Approaches

Richin Sukesh, Mathias Seuret, Anguelos Nicolaou +2

Binarization of document images is an important pre-processing step in the field of document analysis. Traditional image binarization techniques usually rely on histograms or local…

cs.CV2023★ 5 cited

Combining OCR Models for Reading Early Modern Printed Books

Mathias Seuret, Janne van der Loop, Nikolaus Weichselbaumer +6

In this paper, we investigate the usage of fine-grained font recognition on OCR for books printed from the 15th to the 18th century. We used a newly created dataset for OCR of earl…