MMGait provides a new multi-sensor gait dataset and OmniGait baseline to support single-modal, cross-modal, and unified multi-modal person identification from walking patterns.
Paddleseg: A high-efficient development toolkit for image segmentation
3 Pith papers cite this work. Polarity classification is still indexing.
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BarbieGait is a new synthetic gait dataset with identity-consistent cloth changes paired with the GaitCLIF model that improves cross-clothing recognition on the new data and existing benchmarks.
DT-SegNet combines YOLOv5 detection and SegFormer segmentation to outperform Weka and ilastik on precipitate measurement in Cr-based superalloy EM images.
citing papers explorer
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MMGait: Towards Multi-Modal Gait Recognition
MMGait provides a new multi-sensor gait dataset and OmniGait baseline to support single-modal, cross-modal, and unified multi-modal person identification from walking patterns.
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BarbieGait: An Identity-Consistent Synthetic Human Dataset with Versatile Cloth-Changing for Gait Recognition
BarbieGait is a new synthetic gait dataset with identity-consistent cloth changes paired with the GaitCLIF model that improves cross-clothing recognition on the new data and existing benchmarks.
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Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys
DT-SegNet combines YOLOv5 detection and SegFormer segmentation to outperform Weka and ilastik on precipitate measurement in Cr-based superalloy EM images.