Awesome-gait-recognition

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)

• Awesome-gait-recognition
  • Table of Contents (Ongoing updates)
  • 1. Survey
  • 2. arXiv
  • 3. Conference
    • 1. CVPR
    • 2. ICCV
    • 3. AAAI
    • 4. ACM MM
    • 5. ECCV
    • 6. ICME
    • 7. Other Top Conferences
  • 4. Journal
    • 1. TPAMI
    • 2. TIP
    • 3. TIFS
    • 4. PR
    • 5. TMM
    • 6. TCSVT
    • 7. TBIOM
    • 8. Other Top Journals

1. Survey

• Deep Gait Recognition: A Survey. [TPAMI-23][arXiv-22]
• A comprehensive survey on deep gait recognition: algorithms, datasets and challenges. [arXiv-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]
• Combining the Silhouette and Skeleton Data for Gait Recognition [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]
• SkeletonGait: Gait Recognition Using Skeleton Maps. [arXiv-23]

3. Conference

1. CVPR

• Dynamic Aggregated Network for Gait Recognition. [CVPR-23] [Github]

• 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

• GPGait: Generalized Pose-based Gait Recognition. [ICCV-23]
• Physics-Augmented Autoencoder for 3D Skeleton-Based Gait Recognition. [ICCV-23]
• Fine-grained Unsupervised Domain Adaptation for Gait Recognition. [ICCV-23]
• Hierarchical Spatio-Temporal Representation Learning for Gait Recognition. [ICCV-23]
• DyGait: Exploiting Dynamic Representations for High-performance Gait Recognition. [ICCV-23]
• 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

• QAGait: Revisit Gait Recognition From a Quality Perspective. [AAAI-24]
• 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]
• Pose-Based Temporal-Spatial Network (PTSN) for Gait Recognition with Carrying and Clothing Variations. [Biometric Recognition-17]
• 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]

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]
• 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]
• Pose Gait: 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]