Gait Recognition
54 papers with code • 2 benchmarks • 9 datasets
( Image credit: GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition )
Libraries
Use these libraries to find Gait Recognition models and implementations
Gait3D
CASIA-B
TUM-GAID
PsyMo
CCGR
OUMVLP-Pose
Gait3D-Parsing
Most implemented papers
Robust Cross-View Gait Recognition with Evidence: A Discriminant Gait GAN (DiGGAN) Approach
u112358/DiGGAN
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Gait as a biometric trait has attracted much attention in many security and privacy applications such as identity recognition and authentication, during the last few decades.
Deep 1D-Convnet for accurate Parkinson disease detection and severity prediction from gait
To our knowledge, this is the state-of-the-start performance in Parkinson's gait recognition.
Biometrics Recognition Using Deep Learning: A Survey
Deep learning-based models have been very successful in achieving state-of-the-art results in many of the computer vision, speech recognition, and natural language processing tasks in the last few years.
Feature Learning for Accelerometer based Gait Recognition
margitantal68/featurelearning
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Feature extractors using similar architectures incorporated into end-to-end models and autoencoders were compared based on their ability of learning good representations for a gait verification system.
3D Local Convolutional Neural Networks for Gait Recognition
Second, different body parts possess different scales, and even the same part in different frames can appear at different locations and scales.
Multimodal Gait Recognition for Neurodegenerative Diseases
zhaoaite/CorrMNN
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In recent years, single modality based gait recognition has been extensively explored in the analysis of medical images or other sensory data, and it is recognised that each of the established approaches has different strengths and weaknesses.
GaitSet: Cross-view Gait Recognition through Utilizing Gait as a Deep Set
AbnerHqC/GaitSet
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In this paper, we present a novel perspective that utilizes gait as a deep set, which means that a set of gait frames are integrated by a global-local fused deep network inspired by the way our left- and right-hemisphere processes information to learn information that can be used in identification.
TraND: Transferable Neighborhood Discovery for Unsupervised Cross-domain Gait Recognition
Despite significant improvement in gait recognition with deep learning, existing studies still neglect a more practical but challenging scenario -- unsupervised cross-domain gait recognition which aims to learn a model on a labeled dataset then adapts it to an unlabeled dataset.
SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition
In this work, we propose a self-supervised gait recognition method, termed SelfGait, which takes advantage of the massive, diverse, unlabeled gait data as a pre-training process to improve the representation abilities of spatiotemporal backbones.
Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization
jinx-USTC/GI-ReID
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CVPR 2022
Specifically, we introduce Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, we name this framework as GI-ReID.
