mlsanityData to 7 Oct 2026

Egocentric Human-Object Interaction Detection Exploiting Synthetic Data

arXiv 2204.07061 ↗First posted 14 Apr 2022cs.CVcited by 11

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Abstract (arXiv)

We consider the problem of detecting Egocentric HumanObject Interactions (EHOIs) in industrial contexts. Since collecting and labeling large amounts of real images is challenging, we propose a pipeline and a tool to generate photo-realistic synthetic First Person Vision (FPV) images automatically labeled for EHOI detection in a specific industrial scenario. To tackle the problem of EHOI detection, we propose a method that detects the hands, the objects in the scene, and determines which objects are currently involved in an interaction. We compare the performance of our method with a set of state-of-the-art baselines. Results show that using a synthetic dataset improves the performance of an EHOI detection system, especially when few real data are available. To encourage research on this topic, we publicly release the proposed dataset at the following url: https://iplab.dmi.unict.it/EHOI_SYNTH/.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 28 of its 35 references that are in the map. First posted on arXiv 14 Apr 2022.

Builds on

28 of 35 references.

References · 28

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16 more
  1. 2015Visual Semantic Role Labelingcited by 188
  2. 2017GANerated Hands for Real-time 3D Hand Tracking from Monocular RGBcited by 147
  3. 2019PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detectioncited by 143
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  6. 2017Real-time Hand Tracking under Occlusion from an Egocentric RGB-D Sensorcited by 84
  7. 2020The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domaincited by 79
  8. 2019Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsensecited by 71
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  16. 2021The Object at Hand: Automated Editing for Mixed Reality Video Guidance from Hand-Object Interactionscited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 5; 2024: 0; 2025: 2; 2026: 3.

11 papers.