VisionAId is an offline-first Android application that combines six on-device models for depth, segmentation, embeddings, face detection and banknote recognition with a few-shot pipeline that lets users teach the system their personal objects and then guides them to those objects via AR, audio and h
arXiv preprint arXiv:2601.12882 , year =
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Empirical benchmark finds YOLO26 superior on Pascal VOC accuracy and efficiency but YOLOv8 faster on GPU, with both models struggling similarly on VisDrone small-object detection.
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VisionAId: An Offline-First Multimodal Android Assistant for People with Visual Impairment, Featuring Personalized Object Retrieval
VisionAId is an offline-first Android application that combines six on-device models for depth, segmentation, embeddings, face detection and banknote recognition with a few-shot pipeline that lets users teach the system their personal objects and then guides them to those objects via AR, audio and h