AttIncGait: Dual Attention Embedded Inception Framework for Robust Biometric Gait Recognition

Dual Attention Embedded Inception Framework for Robust Biometric Gait Recognition

Results validate the effectiveness of attention-driven multi-scale fusion for gait recognition and highlight the potential of AttIncGait for real-world biometric identification and mobility analysis.

CDGaitFusion: a multimodal gait recognition network based on the fusion of commonality patterns and differential features

CDGaitFusion is introduced, a multimodal gait recognition framework that integrates shared motion patterns with individual-specific features that provides a reliable and extensible framework for mitigating gait feature degradation under complex real-world conditions.

SE-ResAutoNet: an attention and residual learning framework for reliable gait-based suspect identification

Gait recognition relies on the distinctive walking pattern of the individuals that helps to identify the person accurately even in the long distance or in varied environments without any user interaction. Unlike existing techniques, the method works independently, it does not depend on a person engaging or interacting...

RestoreGait: a recognition-oriented temporal inpainting framework for occluded gait recognition

RestoreGait is introduced, an end-to-end framework designed to actively recover occluded gait cues through a lightweight pseudo-3D spatiotemporal decoupled inpainting module that decouples spatial contour restoration from temporal motion aggregation, thereby effectively utilizing visible information across multiple fra...

BigGaitMamba: Foundation-Driven State-Space Temporal Learning for Multi-View Gait Representation and Non-Cooperative Person Identification

Gait biometrics support non-cooperative identification from distant surveillance video, yet viewpoint changes, clothing, carried objects, low resolution, occlusion, and long temporal dependencies reduce recognition reliability. BigGaitMamba addresses these conditions through a unified architecture combining foundation...

Edge-Deployable Dual-Branch Network with Cross-Attention for Multi-Source Gait Recognition