/Awesomegaitrecognition

A collection of AWESOME things about Gait Recognition

Awesome-gait-recognition Awesome

This repo is a collection of AWESOME algorithms about Gait Recognition, including papers, code, etc. Feel free to star and fork.

Table of Contents (Ongoing updates)

1. Survey

  • Deep Gait Recognition: A Survey. [TPAMI-23][arXiv]
  • A comprehensive survey on deep gait recognition: algorithms, datasets and challenges. [arXiv-22]
  • Deep gait recognition: A survey. [TPAMI-22]
  • A survey on gait recognition via wearable sensors. [CSUR-19]
  • A survey on gait recognition. [CSUR-18]
  • Biometric recognition by gait: A survey of modalities and features. [CVIU-18]

2. arXiv

  • GaitGS: Temporal Feature Learning in Granularity and Span Dimension for Gait Recognition. [arXiv-23]
  • GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition. [arXiv-23]
  • Human Body Pose Estimation for Gait Identification: A Comprehensive Survey of Datasets and Models. [arXiv-23]
  • GaitRef: Gait Recognition with Refined Sequential Skeletons. [arXiv-23]
  • Unsupervised Gait Recognition with Selective Fusion. [arXiv-23]
  • GPGait: Generalized Pose-based Gait Recognition. [arXiv-23]
  • GaitEditer: Attribute Editing for Gait Representation Learning. [arXiv-23]
  • Exploring Deep Models for Practical Gait Recognition. [arXiv-23]
  • GaitSADA: Self-Aligned Domain Adaptation for mmWave Gait Recognition. [arXiv-23]
  • Parkinson gait modelling from an anomaly deep representation. [arXiv-23]
  • LiCamGait: Gait Recognition in the Wild by Using LiDAR and Camera Multi-modal Visual Sensors. [arXiv-22]
  • From Indoor To Outdoor: Unsupervised Domain Adaptive Gait Recognition. [arXiv-22]
  • Uncertainty-aware Gait Recognition via Learning from Dirichlet Distribution-based Evidence. [arXiv-22]
  • HDNet: Hierarchical Dynamic Network for Gait Recognition using Millimeter-Wave Radar. [arXiv-22]
  • GaitMixer: Skeleton-based Gait Representation Learning via Wide-spectrum Multi-axial Mixer. [arXiv-22]
  • Motion Matters: A Novel Motion Modeling For Cross-View Gait Feature Learning. [arXiv-22]
  • Multi-view Gait Recognition based on Siamese Vision Transformer. [arXiv-22]
  • CNTN: Cyclic Noise-tolerant Network for Gait Recognition. [arXiv-22]
  • Generalized Inter-class Loss for Gait Recognition. [arXiv-22]
  • Learning Gait Representation from Massive Unlabelled Walking Videos: A Benchmark. [arXiv-22]
  • Spatial Transformer Network on Skeleton-based Gait Recognition. [arXiv-22]

3. Conference

1. CVPR

  • Dynamic Aggregated Network for Gait Recognition. [CVPR-23] [Github] Static Badge
  • An In-Depth Exploration of Person Re-Identification and Gait Recognition in Cloth-Changing Conditions. [CVPR-23] [Github]
  • GaitGCI: Generative Counterfactual Intervention for Gait Recognition. [CVPR-23]
  • LidarGait: Benchmarking 3D Gait Recognition With Point Clouds. [CVPR-23][Github]
  • OpenGait: Revisiting Gait Recognition Towards Better Practicality. [CVPR-23][Github]
  • Multi-Modal Gait Recognition via Effective Spatial-Temporal Feature Fusion. [CVPR-23]
  • Gait Recognition in the Wild With Dense 3D Representations and a Benchmark. [CVPR-22] [Github]
  • Lagrange Motion Analysis and View Embeddings for Improved Gait Recognition.[CVPR-22]
  • Cloth-Changing Person Re-Identification From a Single Image With Gait Prediction and Regularization. [CVPR-22]
  • Towards a Deeper Understanding of Skeleton-based Gait Recognition. [CVPRW-22]
  • Cross-View Gait Recognition With Deep Universal Linear Embeddings. [CVPR-21]
  • Gait Recognition via Semi-supervised Disentangled Representation Learning to Identity and Covariate Features. [CVPR-20]
  • GaitPart: Temporal Part-Based Model for Gait Recognition. [CVPR-20]
  • A geometric convnet on 3d shape manifold for gait recognition. [CVPRW-20]
  • Learning Joint Gait Representation via Quintuplet Loss Minimization. [CVPR-19]
  • Gait Recognition via Disentangled Representation Learning. [CVPR-19]
  • EV-Gait: Event-Based Robust Gait Recognition Using Dynamic Vision Sensors. [CVPR-19]
  • Joint Intensity and Spatial Metric Learning for Robust Gait Recognition. [CVPR-17]
  • GaitGAN: Invariant Gait Feature Extraction Using Generative Adversarial Networks. [CVPRW-17]
  • Gait Recognition under Speed Transition. [CVPR-14]
  • Video from nearly still: An application to low frame-rate gait recognition. [CVPR-12]
  • Gait recognition from time-normalized joint-angle trajectories in the walking plane.[CVPR-01]

2. ICCV

  • Gait Recognition via Effective Global-Local Feature Representation and Local Temporal Aggregation. [ICCV-21]
  • Context-Sensitive Temporal Feature Learning for Gait Recognition. [ICCV-21]
  • 3D Local Convolutional Neural Networks for Gait Recognition. [ICCV-21]
  • Gait Recognition in the Wild: A Benchmark. [ICCV-21]
  • End-to-end Model-based Gait Recognition using Synchronized Multi-view Pose Constraint. [ICCVW-21]

3. AAAI

  • Gait Recognition for Co-Existing Multiple People Using Millimeter Wave Sensing. [AAAI-20]
  • STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits. [AAAI-20]
  • GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition. [AAAI-19]

4. ACM MM

  • Generalized Inter-class Loss for Gait Recognition. [ACM MM-22]
  • Gait recognition in the wild with multi-hop temporal switch. [ACM MM-22]
  • Gait recognition with multiple-temporal-scale 3d convolutional neural network. [ACM MM-20]

5. ECCV

  • MetaGait: Learning to Learn an Omni Sample Adaptive Representation for Gait Recognition. [ECCV-22]
  • GaitEdge: Beyond Plain End-to-End Gait Recognition for Better Practicality. [ECCV-22]
  • Gait Lateral Network: Learning Discriminative and Compact Representations for Gait Recognition. [ECCV-22]
  • Take an Emotion Walk: Perceiving Emotions from Gaits Using Hierarchical Attention Pooling and Affective Mapping. [ECCV-20]
  • Gait Recognition from a Single Image using a Phase-Aware Gait Cycle Reconstruction Network. [ECCV-20]
  • Gait recognition using a view transformation model in the frequency domain. [ECCV-06]

6. ICME

  • Decomposing Identity and View for Cross-View Gait Recognition. [ICME-22]
  • GaitTransformer: Multiple-Temporal-Scale Transformer for Cross-View Gait Recognition. [ICME-22]

7. Other Top Conferences

  • CTrGAN: Cycle Transformers GAN for Gait Transfer. [WACV-23]
  • Long Range Gait Matching Using 3D Body Fitting With Gait-Specific Motion Constraints. [WACV-23]
  • Gait Recognition Using 3-D Human Body Shape Inference. [WACV-23]
  • FedGait: A Benchmark for Federated Gait Recognition. [ICPR-22]
  • Interpretable Gait Recognition by Granger Causality. [ICPR-22]
  • GAITTAKE: Gait recognition by temporal attention and keypoint-guided embedding.[ICIP-22]
  • GaitStrip: Gait Recognition via Effective Strip-based Feature Representations and Multi-Level Framework. [ACCV-22]
  • Silhouette-based view-embeddings for gait recognition under multiple views. [ICIP-21]
  • Real-Time Gait-Based Age Estimation and Gender Classification From a Single Image. [WACV-21]
  • GaitMask: Mask-based Model for Gait Recognition.[BMVC-21]
  • Gaitgraph: Graph convolutional network for skeleton-based gait recognition. [ICIP-21]
  • Part-based collaborative spatio-temporal feature learning for cloth-changing gait recognition. [ICPR-20]
  • Gait recognition using multi-scale partial representation transformation with capsules. [ICPR-20]
  • End-to-end model-based gait recognition. [ACCV-20]
  • Gait energy image restoration using generative adversarial networks. [ICIP-19]
  • Glidar3dj: a view-invariant gait identification via flash lidar data correction. [ICIP-19]
  • Multi-view gait recognition using 3D convolutional neural networks. [ICIP-16]
  • GEINet: View-invariant gait recognition using a convolutional neural network. [ICB-16]
  • Learning effective gait features using LSTM. [ICPR-16]
  • Robust view transformation model for gait recognition. [ICIP-11]
  • Cross view gait recognition using correlation strength. [BMVC-10]
  • A framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition. [ICPR-06]
  • automated model-based extraction and analysis of gait. [AFGR-04] Static Badge

4. Journal

1. TPAMI

  • GaitSet: Cross-view gait recognition through utilizing gait as a deep set. [TPAMI-22]
  • On learning disentangled representations for gait recognition. [TPAMI-20]
  • Multi-gait recognition based on attribute discovery. [TPAMI-17]
  • A comprehensive study on cross-view gait based human identification with deep cnns. [TPAMI-16]
  • Human identification using temporal information preserving gait template. [TPAMI-11]
  • Individual recognition using gait energy image. [TPAMI-06]
  • Silhouette analysis-based gait recognition for human identification. [TPAMI-03]

2. TIP

  • GaitMPL: Gait Recognition with Memory-Augmented Progressive Learning. [TIP-22]
  • Multi-view gait image generation for cross-view gait recognition. [TIP-22]
  • Condition-aware comparison scheme for gait recognition. [TIP-20]
  • Cross-view gait recognition by discriminative feature learning. [TIP-19]
  • Recognizing gaits across views through correlated motion co-clustering. [TIP-14]
  • Gait recognition with shifted energy image and structural feature extraction. [TIP-12]

3. TIFS

  • Occlusion-aware Human Mesh Model-based Gait Recognition. [TIFS-23]
  • GaitReload: A Reloading Framework for Defending Against On-Manifold Adversarial Gait Sequences. [TIFS-23]
  • Joint intensity transformer network for gait recognition robust against clothing and carrying status. [TIFS-19]
  • Skeleton-based gait recognition via robust frame-level matching. [TIFS-19]
  • Multi-task GANs for view-specific feature learning in gait recognition. [TIFS-18]
  • Human identification from freestyle walks using posture-based gait feature. [TIFS-17]
  • Recognizing gaits on spatio-temporal feature domain. [TIFS-14]
  • A new view-invariant feature for cross-view gait recognition.[TIFS-13]
  • Gait recognition using compact feature extraction transforms and depth information. [TIFS-07]

4. PR

  • Temporal sparse adversarial attack on sequence-based gait recognition. [PR-23]
  • GaitSlice: A gait recognition model based on spatio-temporal slice features. [PR-22]
  • Gait recognition invariant to carried objects using alpha blending generative adversarial networks. [PR-22]
  • Symmetry-Driven hyper feature GCN for skeleton-based gait recognition. [PR-22]
  • GaitSlice: A gait recognition model based on spatio-temporal slice features. [PR-22]
  • A unified perspective of classification-based loss and distance-based loss for cross-view gait recognition. [PR-22]
  • Multi-task learning for gait-based identity recognition and emotion recognition using attention enhanced temporal graph convolutional network [PR-21]
  • A model-based gait recognition method with body pose and human prior knowledge. [PR-20]
  • Gaitnet: An end-to-end network for gait based human identification. [PR-19]
  • A comprehensive study on gait biometrics using a joint CNN-based method. [PR-19]
  • Complete canonical correlation analysis with application to multi-view gait recognition. [PR-16]
  • Uncooperative gait recognition by learning to rank. [PR-14]
  • Gait flow image: A silhouette-based gait representation for human identification. [PR-11]
  • Extracting a diagnostic gait signature. [PR-08]

5. TMM

  • Improving Disentangled Representation Learning for Gait Recognition using Group Supervision. [TMM-22]
  • A Strong and Robust Skeleton-based Gait Recognition Method with Gait Periodicity Priors. [TMM-22]
  • Associated spatio-temporal capsule network for gait recognition. [TMM-21]
  • Gait Recognition based on Local Graphical Skeleton Descriptor with Pairwise Similarity Network. [TMM-21]
  • Attentive spatial–temporal summary networks for feature learning in irregular gait recognition][TMM-19 ]

6. TCSVT

  • Enhanced Spatial-Temporal Salience for Cross-view Gait Recognition. [TCSVT-22]
  • Cross-view gait recognition using pairwise spatial transformer networks. [TCSVT-20]
  • Coupled bilinear discriminant projection for cross-view gait recognition. [TCSVT-19]
  • On input/output architectures for convolutional neural network-based cross-view gait recognition. [TCSVT-17]
  • Gait recognition under various viewing angles based on correlated motion regression. [TCSVT-12]
  • Fusion of static and dynamic body biometrics for gait recognition. [TCSVT-04]

7. TBIOM

  • Gait Pyramid Attention Network: Toward Silhouette Semantic Relation Learning for Gait Recognition. [TBIOM-22]
  • STAR: Spatio-Temporal Augmented Relation Network for Gait Recognition. [TBIOM-22]
  • Multi-view large population gait database with human meshes and its performance evaluation. [TBIOM-22]
  • Set residual network for silhouette-based gait recognition. [TBIOM-21]
  • View-invariant gait recognition with attentive recurrent learning of partial representations. [TBIOM-20]
  • Performance evaluation of model-based gait on multi-view very large population database with pose sequences. [TBIOM-20]

8. Other Top Journals

  • Learning Temporal Attention based Keypoint-guided Embedding for Gait Recognition. [JSTSP-23]
  • Gait Quality Aware Network: Toward the Interpretability of Silhouette-Based Gait Recognition. [TNNLS-22]
  • Gait Identification Based on Human Skeleton with Pairwise Graph Convolutional Network. [ICME-21]
  • Static and Dynamic Features Analysis from Human Skeletons for Gait Recognition. [IJCB-21]
  • Gait recognition based on 3d skeleton data and graph convolutional network. [IJCB-20]
  • Dense-view geis set: View space covering for gait recognition based on dense-view gan. [IJCB-20]
  • DeformGait: Gait Recognition under Posture Changes using Deformation Patterns between Gait Feature Pairs. [IJCB-20]
  • Walking speed influences on gait cycle variability. [GP-07]