Describing Common Human Visual Actions in Images
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Abstract (arXiv)
Which common human actions and interactions are recognizable in monocular still images? Which involve objects and/or other people? How many is a person performing at a time? We address these questions by exploring the actions and interactions that are detectable in the images of the MS COCO dataset. We make two main contributions. First, a list of 140 common `visual actions', obtained by analyzing the largest on-line verb lexicon currently available for English (VerbNet) and human sentences used to describe images in MS COCO. Second, a complete set of annotations for those `visual actions', composed of subject-object and associated verb, which we call COCO-a (a for `actions'). COCO-a is larger than existing action datasets in terms of number of actions and instances of these actions, and is unique because it is data-driven, rather than experimenter-biased. Other unique features are that it is exhaustive, and that all subjects and objects are localized. A statistical analysis of the accuracy of our annotations and of each action, interaction and subject-object combination is provided.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Jun 2015.
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Citing papers per year: 2021: 1; 2022: 4; 2023: 3; 2024: 1; 2025: 2; 2026: 1.
12 papers.
- 2022Measuring Representational Harms in Image Captioningcited by 36
- 2022Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactionscited by 34
- 2024JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context and Dynamics of Human Interactions Within Social Groupscited by 13
- 2022Ambiguous Images With Human Judgments for Robust Visual Event Classificationcited by 12
- 2021Visual Question Answering: which investigated applications?cited by 11
- 2022Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?cited by 8
- 2023Learning Human-Human Interactions in Images from Weak Textual Supervisioncited by 3
- 2026Seeing vs. Believing: Evaluating the Language Bias of Open-Source MLLMs in Counter-Intuitive Scenescited by 2
- 2023NeSy4VRD: A Multifaceted Resource for Neurosymbolic AI Research using Knowledge Graphs in Visual Relationship Detectioncited by 0
- 2023Human Action Co-occurrence in Lifestyle Vlogs using Graph Link Predictioncited by 0
- 2025When concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?cited by 0
- 2025Towards Robust Evaluation of Visual Activity Recognition: Resolving Verb Ambiguity with Sense Clusteringcited by 0
- 2026Seeing vs. Believing: Evaluating the Language Bias of Open-Source MLLMs in Counter-Intuitive Scenes12 Jan 2026
- 2025Towards Robust Evaluation of Visual Activity Recognition: Resolving Verb Ambiguity with Sense Clustering7 Aug 2025
- 2025When concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?22 Jun 2025
- 2024JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context and Dynamics of Human Interactions Within Social Groups6 Apr 2024
- 2023Human Action Co-occurrence in Lifestyle Vlogs using Graph Link Prediction12 Sep 2023
- 2023NeSy4VRD: A Multifaceted Resource for Neurosymbolic AI Research using Knowledge Graphs in Visual Relationship Detection22 May 2023
- 2023Learning Human-Human Interactions in Images from Weak Textual Supervision27 Apr 2023
- 2022Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?21 Oct 2022
- 2022Ambiguous Images With Human Judgments for Robust Visual Event Classification6 Oct 2022
- 2022Measuring Representational Harms in Image Captioning14 Jun 2022
- 2022Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions27 May 2022
- 2021Visual Question Answering: which investigated applications?4 Mar 2021