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New dataset and framework advance multilingual person retrieval

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced MultiPedes, a new large-scale dataset for multilingual text-based person retrieval, addressing the limitations of previous English-only approaches. The dataset comprises 10 million image-text pairs across four languages, constructed using a quality-aware pipeline. Alongside the dataset, the team developed ViSeLA, a novel framework that enhances multilingual feature learning through a semantic-aware module and improves cross-modal alignment with a vision-grounded semantic probe, eliminating the need for a pivot language. AI

IMPACT Advances multilingual capabilities in computer vision and information retrieval tasks.

RANK_REASON The cluster describes a new academic paper introducing a novel dataset and framework for a specific AI task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New dataset and framework advance multilingual person retrieval

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The cluster describes a new academic paper introducing a novel dataset and framework for a specific AI task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Mang Ye ·

    Vision-Grounded Semantic Learning and Alignment for Scalable Multilingual Text-Based Person Retrieval

    Multilingual Text-Based Person Retrieval (TBPR) aims to retrieve individuals with texts in multiple languages. Despite its practical importance, it has been overlooked by existing research, which mainly focuses on English-only retrieval. The only prior attempt at multilingual TBP…

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