Handwriting Verification
5 papers with code • 2 benchmarks • 5 datasets
The goal of handwriting verification is to find a measure of confidence whether the given handwritten samples are written by the same or different writer.
Benchmarks
These leaderboards are used to track progress in Handwriting Verification
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CEDAR Signature
AND Dataset
BRUSH
DigiLeTs
Most implemented papers
SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification
Offline signature verification is one of the most challenging tasks in biometrics and document forensics.
Hybrid Feature Learning for Handwriting Verification
Experiments are performed by complementing one of the HEF methods with one ALF method on 150000 pairs of samples of the word "AND" cropped from handwritten notes written by 1500 writers.
Explanation based Handwriting Verification
The dataset is released for publicuse and the methods can be extended to provide explanations on other verification taskslike face verification and bio-medical comparison.
Attention based Writer Independent Handwriting Verification
mshaikh2/AttentionHandwritingVerification
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The task of writer verification is to provide a likelihood score for whether the queried and known handwritten image samples belong to the same writer or not.
MSDS: A Large-Scale Chinese Signature and Token Digit String Dataset for Handwriting Verification
MSDS-ChS consists of handwritten Chinese signatures, which, to the best of our knowledge, is the largest publicly available Chinese signature dataset for handwriting verification, at least eight times larger than existing online datasets.
