In practical gait recognition scenarios where only silhouette sequences are available without original videos, directly applying appearance-driven BigGait frameworks often leads to a mismatch between methodology and data conditions. To leverage the prior advantages of frozen Large Vision Models (LVMs) for universal fea...
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.
Gait recognition has achieved remarkable success in constrained environments, yet its performance often degrades significantly in cross-domain and cross-vertical-view scenarios. This is primarily due to the fact that domain-specific silhouette geometry causes models to overfit to extrinsic geometric characteristics rat...
Advances in artificial intelligence have made hand gesture recognition an important human–computer interaction modality. Graph convolutional networks (GCNs) are widely used for skeleton-based hand gesture recognition, yet their performance can be limited by weak semantic topology modeling, underused feature channels, a...
A three-stage Adaptive CNN-Enhanced Scale-fusion Network (ACESNet) for six-channel accelerometer–gyroscope activity recognition supports a favorable performance–efficiency trade-off relative to the selected baselines under the stated protocol.
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