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September 29, 2025Open Access

Exploring Generalized Gait Recognition: Reducing Redundancy and Noise within Indoor and Outdoor Datasets

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This approach improves cross-domain gait recognition using dataset distillation and a novel loss function.

The proposed framework significantly enhances recognition performance across varied datasets and domains.
Experiments showed improvements in cross-dataset recognition for methods like GaitBase and DeepGaitV2.
Using a disentangled triplet loss, the approach minimizes optimization conflicts from multiple datasets.
The strategy filters out unhelpful training samples, boosting data efficiency by removing the least informative ones.

Zhou et al. (2025) studied this question.

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