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New methods tackle 2D-3D cross-modal gait recognition

By PulseAugur Editorial · [2 sources] ·

Two new research papers introduce novel approaches to cross-modal gait recognition, aiming to improve the identification of individuals across different sensing modalities like 2D cameras and 3D LiDAR. DiffCrossGait utilizes latent diffusion models to align gait trajectories at a fundamental level, rather than just final embeddings, promoting modality-invariant features. TCFDNet employs text-guided feature disentanglement, using large language models to generate semantic descriptions of gait patterns and align visual and textual features for more robust recognition. AI

IMPACT These new techniques could enhance biometric security and surveillance systems by enabling more accurate identification across diverse sensor inputs.

RANK_REASON Two academic papers published on arXiv present novel methods for cross-modal gait recognition.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New methods tackle 2D-3D cross-modal gait recognition

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Two academic papers published on arXiv present novel methods for cross-modal gait recognition.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Zhiyang Lu, Ming Cheng ·

    DiffCrossGait: Trajectory-Level Alignment for 2D-3D Cross-Modal Gait Recognition via Latent Diffusion

    arXiv:2606.00153v1 Announce Type: cross Abstract: Cross-modal 2D-3D gait recognition is impeded by inherent domain discrepancies between 2D silhouette and 3D LiDAR range-view representations. While prior methods align only final embeddings, we propose DiffCrossGait, which reformu…

  2. arXiv cs.CV TIER_1 English(EN) · Zhiyang Lu, Ming Cheng ·

    Text-guided Feature Disentanglement for Cross-modal Gait Recognition

    arXiv:2605.30784v1 Announce Type: new Abstract: Gait recognition is a biometric technique that identifies individuals based on their walking patterns, offering advantages in long-range, non-intrusive scenarios. However, real-world scenarios often involve heterogeneous sensing mod…

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