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Evidence record 7656 · automatically gathered

UniPAR: A Unified Framework for Pedestrian Attribute Recognition

Pedestrian Attribute Recognition is a foundational computer vision task that provides essential support for downstream applications, including person retrieval in video surveillance and intelligent retail analytics. However, existing research is frequently constrained by the ``one-model-per-dataset" paradigm and struggles to handle significant discrepancies across domains in terms of modalities, attribute definitions, and environmental scenarios. To address these challenges, we propose UniPAR, a

Record details

Published: 5 March 2026
Source: arXiv
Category: Research
Topics: Privacy · Environment
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (5 March 2026), “UniPAR: A Unified Framework for Pedestrian Attribute Recognition,” evidence record 7656, https://ethics.ai/record/7656 (originally published by arXiv).

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