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New benchmark tackles semi-supervised multi-modal crowd counting

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced the first benchmark for semi-supervised multi-modal crowd counting. This new benchmark defines the task's setting and a standardized protocol for data partitioning. It also includes an evaluation of baseline methods, comprising existing supervised multi-modal techniques and semi-supervised single-modal approaches. AI

IMPACT Establishes a new evaluation framework for crowd counting tasks, potentially improving AI model performance in this area.

RANK_REASON The cluster contains an academic paper detailing a new benchmark and evaluation protocol.

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Haoliang Meng, Xiaopeng Hong, Yabin Wang, Wangmeng Zuo ·

    A Benchmark for Semi-supervised Multi-modal Crowd Counting

    arXiv:2606.03646v1 Announce Type: new Abstract: This paper constructs the first benchmark on semi-supervised multi-modal crowd counting. To lay the foundation for this unexplored task, we first formulate the semi-supervised multi-modal setting and a standardized protocol that spe…

  2. arXiv cs.CV TIER_1 English(EN) · Wangmeng Zuo ·

    A Benchmark for Semi-supervised Multi-modal Crowd Counting

    This paper constructs the first benchmark on semi-supervised multi-modal crowd counting. To lay the foundation for this unexplored task, we first formulate the semi-supervised multi-modal setting and a standardized protocol that specifies the labeled-unlabeled data partition acro…

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