# Deep Learning Methods for Signature Verification

arXiv: https://arxiv.org/abs/1912.05435 · HTML: https://mlsanity.com/paper/1912.05435/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Dec 2019.

## Built on by (most cited first, 1 of 1)

- [Online Handwritten Signature Verification Based on Temporal-Spatial Graph Attention Transformer](https://mlsanity.com/paper/2510.19321/) (2025)

## Abstract (arXiv)

Signature is widely used in human daily lives, and serves as a supplementary characteristic for verifying human identity. However, there is rare work of verifying signature. In this paper, we propose a few deep learning architectures to tackle this task, ranging from CNN, RNN to CNN-RNN compact model. We also improve Path Signature Features by encoding temporal information in order to enlarge the discrepancy between genuine and forgery signatures. Our numerical experiments demonstrate the effectiveness of our constructed models and features representations.