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.
Biggergait: Un- locking gait recognition with layer-wise representations from large vision models
3 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 3years
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GaitProtector optimizes diffusion model latents to impersonate target identities in gait sequences, dropping Rank-1 identification accuracy from 89.6% to 15.0% on CASIA-B while keeping scoliosis diagnostic accuracy at 74.2%.
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.
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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GaitProtector: Impersonation-Driven Gait De-Identification via Training-Free Diffusion Latent Optimization
GaitProtector optimizes diffusion model latents to impersonate target identities in gait sequences, dropping Rank-1 identification accuracy from 89.6% to 15.0% on CASIA-B while keeping scoliosis diagnostic accuracy at 74.2%.
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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.