https://github.com/AbnerHqC/GaitSet
공식 코드GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition
Papers with Code 아카이브
Gait Recognition
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<span style="color:grey; opacity: 0.6">( Image credit: GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/EchoItLiu/SelfGait
공식 코드SelfGait: A Spatiotemporal Representation Learning Method for Self-supervised Gait Recognition
https://github.com/Gait3D/Gait3D-Benchmark
공식 코드Gait Recognition in the Wild with Dense 3D Representations and A Benchmark
https://github.com/JinkaiZheng/TraND
공식 코드TraND: Transferable Neighborhood Discovery for Unsupervised Cross-domain Gait Recognition
https://github.com/Marsrocky/GaitFi
공식 코드GaitFi: Robust Device-Free Human Identification via WiFi and Vision Multimodal Learning
https://github.com/UNB-StepUP/StepUP-P150
공식 코드UNB StepUP: A footStep database for gait analysis and recognition using Underfoot Pressure
https://github.com/ZoeyZheng0/GaitSTR
공식 코드GaitSTR: Gait Recognition with Sequential Two-stream Refinement
https://github.com/ayush-00/mimicgait
공식 코드https://github.com/bb12346/gaitgl
공식 코드GaitGL: Learning Discriminative Global-Local Feature Representations for Gait Recognition
https://github.com/bgdpgz/glgait
공식 코드GLGait: A Global-Local Temporal Receptive Field Network for Gait Recognition in the Wild
https://github.com/bnu-ivc/fastposegait
공식 코드https://github.com/cosmaadrian/psymo
공식 코드PsyMo: A Dataset for Estimating Self-Reported Psychological Traits from Gait
https://github.com/ctrasd/gait-view
공식 코드Silhouette based View embeddings for Gait Recognition under Multiple Views
https://github.com/exitudio/GaitSADA
공식 코드GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition
https://github.com/exitudio/gaitmixer
공식 코드GaitMixer: Skeleton-based Gait Representation Learning via Wide-spectrum Multi-axial Mixer
https://github.com/feng-xueling/trigait
공식 코드TriGait: Aligning and Fusing Skeleton and Silhouette Gait Data via a Tri-Branch Network
https://github.com/gudaochangsheng/HSTL
공식 코드Hierarchical Spatio-Temporal Representation Learning for Gait Recognition
https://github.com/gudaochangsheng/ourcode
공식 코드GaitMM: Multi-Granularity Motion Sequence Learning for Gait Recognition
https://github.com/guxinqian/simple-ccreid
공식 코드Clothes-Changing Person Re-identification with RGB Modality Only
https://github.com/haidongz-usc/GaitRef
공식 코드https://github.com/haijun-xiong/gaitgs
공식 코드GaitGS: Temporal Feature Learning in Granularity and Span Dimension for Gait Recognition
https://github.com/haku-huang/h-more
공식 코드H-MoRe: Learning Human-centric Motion Representation for Action Analysis
https://github.com/hcvlab/hybridgait
공식 코드https://github.com/imanneelmaachi/Parkinson-disease-detection-and-severity-prediction-from-gait
공식 코드Deep 1D-Convnet for accurate Parkinson disease detection and severity prediction from gait
https://github.com/jinx-USTC/GI-ReID
공식 코드Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and Regularization
https://github.com/m-candy77/gaitstrip
공식 코드https://github.com/margitantal68/featurelearning
공식 코드https://github.com/mk-minchul/kprpe
공식 코드https://github.com/oliverhxh/cag
공식 코드Condition-Adaptive Graph Convolution Learning for Skeleton-Based Gait Recognition
https://github.com/prevso1088/open-set-biometrics
공식 코드https://github.com/qinnzou/Gait-Recognition-Using-Smartphones
공식 코드Deep Learning-Based Gait Recognition Using Smartphones in the Wild
https://github.com/rmazzier/OpenSetGaitRecognition_PCAA
공식 코드Open-Set Gait Recognition from Sparse mmWave Radar Point Clouds
https://github.com/shinanzou/ccgr
공식 코드https://github.com/shinanzou/msaff
공식 코드A Multi-Stage Adaptive Feature Fusion Neural Network for Multimodal Gait Recognition
https://github.com/shiqiyu/opengait
공식 코드GaitEdge: Beyond Plain End-to-end Gait Recognition for Better Practicality
https://github.com/take2rohit/poise
공식 코드POISE: Pose Guided Human Silhouette Extraction under Occlusions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.