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

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.

SSM-Gait: multi-modal gait recognition via selective state space fusion and noise isolation

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

AttIncGait is introduced, a deep learning framework that integrates Inception-based multi-scale feature extraction with dual-path attention for effective gait recognition and validates the effectiveness of attention-driven multi-scale fusion.

MMGait: Benchmarking and Unifying Gait Recognition across Heterogeneous Modalities

Gait recognition is commonly studied using RGB videos or their derived silhouettes and poses. Yet human walking produces heterogeneous photometric, geometric, and motion cues that cannot be systematically examined with RGB-centered benchmarks. We present MMGait, a large-scale multi-sensor benchmark that brings visible,...

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...

SpecGait: spatial coordinate aggregation and dynamic-static decoupling network for in-the-wild gait recognition

As a non-contact long-distance biometric identification technology, gait recognition has significant advantages in the field of public safety. However, when landing in the field scene, it is disturbed by covariates, and there is a problem of gait feature extraction distortion. The existing methods are difficult to capt...