mlsanityData to 14 Oct 2026

Semi-Supervised 3D Hand Shape and Pose Estimation with Label Propagation

arXiv 2111.15199 ↗First posted 30 Nov 2021cs.CVcited by 1

Not on the map. Why?

Abstract (arXiv)

To obtain 3D annotations, we are restricted to controlled environments or synthetic datasets, leading us to 3D datasets with less generalizability to real-world scenarios. To tackle this issue in the context of semi-supervised 3D hand shape and pose estimation, we propose the Pose Alignment network to propagate 3D annotations from labelled frames to nearby unlabelled frames in sparsely annotated videos. We show that incorporating the alignment supervision on pairs of labelled-unlabelled frames allows us to improve the pose estimation accuracy. Besides, we show that the proposed Pose Alignment network can effectively propagate annotations on unseen sparsely labelled videos without fine-tuning.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 24 of its 32 references that are in the map. First posted on arXiv 30 Nov 2021.

Builds on

24 of 32 references.

References · 24

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2017PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenescited by 775
  4. 2019Learning joint reconstruction of hands and manipulated objectscited by 378
  5. 2019FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape from Single RGB Imagescited by 271
  6. 2020InterHand2.6M: A Dataset and Baseline for 3D Interacting Hand Pose Estimation from a Single RGB Imagecited by 245
  7. 2017Learning to Estimate 3D Hand Pose from Single RGB Imagescited by 234
  8. 2017Hand Keypoint Detection in Single Images using Multiview Bootstrappingcited by 231
  9. 2017First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotationscited by 230
  10. 20193D Hand Shape and Pose from Images in the Wildcited by 190
  11. 20193D Hand Shape and Pose Estimation from a Single RGB Imagecited by 174
  12. 2020Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wildcited by 146
12 more
  1. 2021Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Timecited by 141
  2. 2020Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstructioncited by 139
  3. 2019End-to-end Hand Mesh Recovery from a Monocular RGB Imagecited by 124
  4. 2019Pushing the Envelope for RGB-based Dense 3D Hand Pose Estimation via Neural Renderingcited by 115
  5. 2018Hand Pose Estimation via Latent 2.5D Heatmap Regressioncited by 111
  6. 2020Weakly Supervised 3D Hand Pose Estimation via Biomechanical Constraintscited by 97
  7. 2018Cross-modal Deep Variational Hand Pose Estimationcited by 89
  8. 2021Model-based 3D Hand Reconstruction via Self-Supervised Learningcited by 65
  9. 2018Disentangling Latent Hands for Image Synthesis and Pose Estimationcited by 44
  10. 2017Using a single RGB frame for real time 3D hand pose estimation in the wildcited by 39
  11. 2019Learning Temporal Pose Estimation from Sparsely-Labeled Videoscited by 39
  12. 2019Single Image 3D Hand Reconstruction with Mesh Convolutionscited by 32

Built on by

Cited by year

Citing papers per year: 2022: 1.

1 paper.

  1. 2022S2Contact: Graph-based Network for 3D Hand-Object Contact Estimation with Semi-Supervised Learningcited by 8