Gait Recognition
20 papers with code • 1 benchmarks • 6 datasets
( Image credit: GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition )
USF
TUM-GAID
CASIA-B
OUMVLP-Pose
Most implemented papers
GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition
AbnerHqC/GaitSet
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In this paper we present a novel perspective, where a gait is regarded as a set consisting of independent frames.
GaitGraph: Graph Convolutional Network for Skeleton-Based Gait Recognition
tteepe/GaitGraph
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However, silhouette images can lose fine-grained spatial information, and most papers do not regard how to obtain these silhouettes in complex scenes.
Towards a Deeper Understanding of Skeleton-based Gait Recognition
Gait recognition is a promising biometric with unique properties for identifying individuals from a long distance by their walking patterns.
Deep Learning-Based Gait Recognition Using Smartphones in the Wild
qinnzou/Gait-Recognition-Using-Smartphones
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Specifically, a hybrid deep neural network is proposed for robust gait feature representation, where features in the space and time domains are successively abstracted by a convolutional neural network and a recurrent neural network.
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.
GaitPart: Temporal Part-Based Model for Gait Recognition
ChaoFan96/GaitPart
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CVPR 2020
Gait recognition, applied to identify individual walking patterns in a long-distance, is one of the most promising video-based biometric technologies.
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.
iLGaCo: Incremental Learning of Gait Covariate Factors
In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset.
