# Multi-Branch with Attention Network for Hand-Based Person Recognition

arXiv: https://arxiv.org/abs/2108.02234 · HTML: https://mlsanity.com/paper/2108.02234/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 16 references that are in the map.
- First posted on arXiv 4 Aug 2021.

## Builds on (most cited first, 11 of 11)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Rethinking the Inception Architecture for Computer Vision](https://mlsanity.com/paper/1512.00567/) (2015)
- [Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning](https://mlsanity.com/paper/1602.07261/) (2016)
- [Self-Attention with Relative Position Representations](https://mlsanity.com/paper/1803.02155/) (2018)
- [Transformers in Vision: A Survey](https://mlsanity.com/paper/2101.01169/) (2021)
- [Bag of Tricks and A Strong Baseline for Deep Person Re-identification](https://mlsanity.com/paper/1903.07071/) (2019)
- [ABD-Net: Attentive but Diverse Person Re-Identification](https://mlsanity.com/paper/1908.01114/) (2019)
- [Relation-Aware Global Attention for Person Re-identification](https://mlsanity.com/paper/1904.02998/) (2019)
- [11K Hands: Gender recognition and biometric identification using a large dataset of hand images](https://mlsanity.com/paper/1711.04322/) (2017)
- [Global Self-Attention Networks for Image Recognition](https://mlsanity.com/paper/2010.03019/) (2020)
- [Hand-Based Person Identification using Global and Part-Aware Deep Feature Representation Learning](https://mlsanity.com/paper/2101.05260/) (2021)

## Built on by (most cited first, 3 of 3)

- [Joint Person Identity, Gender and Age Estimation from Hand Images using Deep Multi-Task Representation Learning](https://mlsanity.com/paper/2303.15263/) (2023)
- [Local-Aware Global Attention Network for Person Re-Identification Based on Body and Hand Images](https://mlsanity.com/paper/2209.04821/) (2022)
- [CLIP-HandID: Vision-Language Model for Hand-Based Person Identification](https://mlsanity.com/paper/2506.12447/) (2025)

## Abstract (arXiv)

In this paper, we propose a novel hand-based person recognition method for the purpose of criminal investigations since the hand image is often the only available information in cases of serious crime such as sexual abuse. Our proposed method, Multi-Branch with Attention Network (MBA-Net), incorporates both channel and spatial attention modules in branches in addition to a global (without attention) branch to capture global structural information for discriminative feature learning. The attention modules focus on the relevant features of the hand image while suppressing the irrelevant backgrounds. In order to overcome the weakness of the attention mechanisms, equivariant to pixel shuffling, we integrate relative positional encodings into the spatial attention module to capture the spatial positions of pixels. Extensive evaluations on two large multi-ethnic and publicly available hand datasets demonstrate that our proposed method achieves state-of-the-art performance, surpassing the existing hand-based identification methods.