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MC-hands-1M: A glove-wearing hand dataset for pose estimation

arXiv 2210.10428 ↗First posted 19 Oct 2022cs.CVcited by 0

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Abstract (arXiv)

Nowadays, the need for large amounts of carefully and complexly annotated data for the training of computer vision modules continues to grow. Furthermore, although the research community presents state of the art solutions to many problems, there exist special cases, such as the pose estimation and tracking of a glove-wearing hand, where the general approaches tend to be unable to provide an accurate solution or fail completely. In this work, we are presenting a synthetic dataset1 for 3D pose estimation of glove-wearing hands, in order to depict the value of data synthesis in computer vision. The dataset is used to fine-tune a public hand joint detection model, achieving significant performance in both synthetic and real images of glove-wearing hands.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 13 of its 15 references that are in the map. First posted on arXiv 19 Oct 2022.

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13 of 15 references.

References · 13

  1. 2018Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomizationcited by 292
  2. 2020InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Imagecited by 244
  3. 2017Learning to Estimate 3D Hand Pose from Single RGB Imagescited by 234
  4. 2017Hand Keypoint Detection in Single Images using Multiview Bootstrappingcited by 231
  5. 20193D Hand Shape and Pose Estimation from a Single RGB Imagecited by 174
  6. 2017GANerated Hands for Real-time 3D Hand Tracking from Monocular RGBcited by 147
  7. 2019H+O: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactionscited by 139
  8. 2020Monocular Real-time Hand Shape and Motion Capture using Multi-modal Datacited by 106
  9. 2018Cross-modal Deep Variational Hand Pose Estimationcited by 89
  10. 2017BigHand2.2M Benchmark: Hand Pose Dataset and State of the Art Analysiscited by 46
  11. 2018Learning to Segment via Cut-and-Pastecited by 42
  12. 20143D Hand Pose Detection in Egocentric RGB-D Imagescited by 17
1 more
  1. 2016Play and Learn: Using Video Games to Train Computer Vision Modelscited by 16

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