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".