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20172026
most citedICDAR 2019 Competition on Image Retrieval for Historical Handwritten Documents

35 citations · 66 across the 9 of their papers we have counts for

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17 papers · 1 filter

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

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.CV20246 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.CV20222 cited

TorMentor: Deterministic dynamic-path, data augmentations with fractals

Anguelos Nicolaou, Vincent Christlein, Edgar Riba +3

We propose the use of fractals as a means of efficient data augmentation. Specifically, we employ plasma fractals for adapting global image augmentation transformations into contin…