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New MObyGaze dataset tackles gender objectification in films

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced the MObyGaze dataset, a comprehensive collection of film data designed to analyze and quantify gender representation disparities and objectification. The dataset includes over 43 hours of video from 20 movies, meticulously annotated by experts with fine-grained localization and categorization of objectification levels and concepts across visual, speech, and audio modalities. The study also formulates learning tasks, investigates methods for handling diverse labels from a small annotator pool, and benchmarks recent vision, text, and audio models to demonstrate the feasibility of this new AI task. AI

IMPACT Provides a new dataset for AI research into understanding and quantifying complex social constructs like objectification in media.

RANK_REASON The cluster describes a new academic dataset and associated research paper, fitting the research bucket. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

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

New MObyGaze dataset tackles gender objectification in films

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The cluster describes a new academic dataset and associated research paper, fitting the research bucket. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Julie Tores, Elisa Ancarani, Lucile Sassatelli, Hui-Yin Wu, Clement Bergman, Lea Andolfi, Victor Ecrement, Remy Sun, Frederic Precioso, Thierry Devars, Magali Guaresi, Virginie Julliard, Sarah Lecossais ·

    MObyGaze: a film dataset of multimodal objectification densely annotated by experts

    arXiv:2505.22084v2 Announce Type: replace Abstract: Characterizing and quantifying gender representation disparities in audiovisual storytelling contents is necessary to grasp how stereotypes may perpetuate on screen. In this article, we consider the high-level construct of objec…

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