FastPoseGait: A Toolbox and Benchmark for Efficient Pose-based Gait Recognition
Shibei Meng, Yang Fu, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang

TL;DR
FastPoseGait is an open-source, modular toolbox that consolidates state-of-the-art pose-based gait recognition algorithms and benchmarks, facilitating research, comparison, and development in the field.
Contribution
It provides a unified framework with multiple algorithms, pre-trained models, and detailed benchmarks to advance pose-based gait recognition research.
Findings
Supports various SOTA algorithms within a unified framework
Provides extensive pre-trained models and benchmark results
Facilitates reproducibility and comparison in gait recognition research
Abstract
We present FastPoseGait, an open-source toolbox for pose-based gait recognition based on PyTorch. Our toolbox supports a set of cutting-edge pose-based gait recognition algorithms and a variety of related benchmarks. Unlike other pose-based projects that focus on a single algorithm, FastPoseGait integrates several state-of-the-art (SOTA) algorithms under a unified framework, incorporating both the latest advancements and best practices to ease the comparison of effectiveness and efficiency. In addition, to promote future research on pose-based gait recognition, we provide numerous pre-trained models and detailed benchmark results, which offer valuable insights and serve as a reference for further investigations. By leveraging the highly modular structure and diverse methods offered by FastPoseGait, researchers can quickly delve into pose-based gait recognition and promote development in…
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Taxonomy
TopicsGait Recognition and Analysis · Human Pose and Action Recognition · Diabetic Foot Ulcer Assessment and Management
MethodsFocus
