MMGait provides a new multi-sensor gait dataset and OmniGait baseline to support single-modal, cross-modal, and unified multi-modal person identification from walking patterns.
Ex- ploring deep models for practical gait recognition
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BarbieGait is a new synthetic gait dataset with identity-consistent cloth changes paired with the GaitCLIF model that improves cross-clothing recognition on the new data and existing benchmarks.
Transfer learning on a new clinical gait dataset shows selective freezing of low-level features in pretrained models yields stable frailty classification, with model attention aligning to lower-limb biomechanics.
A transformer-based model that jointly processes 2D silhouettes and 3D SMPL features outperforms prior single-modality methods on the BRIAR dataset for gait recognition while also estimating age, BMI, and gender.
citing papers explorer
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MMGait: Towards Multi-Modal Gait Recognition
MMGait provides a new multi-sensor gait dataset and OmniGait baseline to support single-modal, cross-modal, and unified multi-modal person identification from walking patterns.
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BarbieGait: An Identity-Consistent Synthetic Human Dataset with Versatile Cloth-Changing for Gait Recognition
BarbieGait is a new synthetic gait dataset with identity-consistent cloth changes paired with the GaitCLIF model that improves cross-clothing recognition on the new data and existing benchmarks.
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The Gait Signature of Frailty: Transfer Learning based Deep Gait Models for Scalable Frailty Assessment
Transfer learning on a new clinical gait dataset shows selective freezing of low-level features in pretrained models yields stable frailty classification, with model attention aligning to lower-limb biomechanics.
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Combo-Gait: Unified Transformer Framework for Multi-Modal Gait Recognition and Attribute Analysis
A transformer-based model that jointly processes 2D silhouettes and 3D SMPL features outperforms prior single-modality methods on the BRIAR dataset for gait recognition while also estimating age, BMI, and gender.