Hierarchical Instance Tracking to Balance Privacy Preservation with Accessible Information

Fuente: arXiv
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Auteurs principaux: Prasad, Neelima, Reynolds, Jarek, Karsanbhai, Neel, Sharma, Tanusree, Zhang, Lotus, Stangl, Abigale, Wang, Yang, Findlater, Leah, Gurari, Danna
Format: Preprint
Publié: 2025
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author Prasad, Neelima
Reynolds, Jarek
Karsanbhai, Neel
Sharma, Tanusree
Zhang, Lotus
Stangl, Abigale
Wang, Yang
Findlater, Leah
Gurari, Danna
author_facet Prasad, Neelima
Reynolds, Jarek
Karsanbhai, Neel
Sharma, Tanusree
Zhang, Lotus
Stangl, Abigale
Wang, Yang
Findlater, Leah
Gurari, Danna
contents We propose a novel task, hierarchical instance tracking, which entails tracking all instances of predefined categories of objects and parts, while maintaining their hierarchical relationships. We introduce the first benchmark dataset supporting this task, consisting of 2,765 unique entities that are tracked in 552 videos and belong to 40 categories (across objects and parts). Evaluation of seven variants of four models tailored to our novel task reveals the new dataset is challenging. Our dataset is available at https://vizwiz.org/tasks-and-datasets/hierarchical-instance-tracking/
format Preprint
id arxiv_https___arxiv_org_abs_2512_10102
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Hierarchical Instance Tracking to Balance Privacy Preservation with Accessible Information
Prasad, Neelima
Reynolds, Jarek
Karsanbhai, Neel
Sharma, Tanusree
Zhang, Lotus
Stangl, Abigale
Wang, Yang
Findlater, Leah
Gurari, Danna
Computer Vision and Pattern Recognition
We propose a novel task, hierarchical instance tracking, which entails tracking all instances of predefined categories of objects and parts, while maintaining their hierarchical relationships. We introduce the first benchmark dataset supporting this task, consisting of 2,765 unique entities that are tracked in 552 videos and belong to 40 categories (across objects and parts). Evaluation of seven variants of four models tailored to our novel task reveals the new dataset is challenging. Our dataset is available at https://vizwiz.org/tasks-and-datasets/hierarchical-instance-tracking/
title Hierarchical Instance Tracking to Balance Privacy Preservation with Accessible Information
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2512.10102