TAMPAR: Visual Tampering Detection for Parcels Logistics in Postal Supply Chains
TAMPAR: Visual Tampering Detection for Parcels Logistics in Postal Supply Chains
TAMPAR is a real-world dataset of parcel photos for tampering detection with annotations in COCO format. For details see our paper and for visual samples our project page. Features are: >900 annotated real-world images with >2,700 visible parcel side surfaces 6 different tampering types 6 different distortion strengths Relevant computer vision tasks: bounding box detection classification instance segmentation keypoint estimation tampering detection and classification If you use this resource for scientific research, please consider citing our WACV 2024 paper "TAMPAR: Visual Tampering Detection for Parcel Logistics in Postal Supply Chains".
parcel, machine learning, logistics, instance segmentation, deep learning, keypoint estimation, computer vision
parcel, machine learning, logistics, instance segmentation, deep learning, keypoint estimation, computer vision
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