mlsanityData to 7 Oct 2026

hSMAL: Detailed Horse Shape and Pose Reconstruction for Motion Pattern Recognition

arXiv 2106.10102 ↗First posted 18 Jun 2021cs.CVcited by 18

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Abstract (arXiv)

In this paper we present our preliminary work on model-based behavioral analysis of horse motion. Our approach is based on the SMAL model, a 3D articulated statistical model of animal shape. We define a novel SMAL model for horses based on a new template, skeleton and shape space learned from 37 horse toys. We test the accuracy of our hSMAL model in reconstructing a horse from 3D mocap data and images. We apply the hSMAL model to the problem of lameness detection from video, where we fit the model to images to recover 3D pose and train an ST-GCN network on pose data. A comparison with the same network trained on mocap points illustrates the benefit of our approach.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 9 of its 21 references that are in the map. First posted on arXiv 18 Jun 2021.

Builds on

9 of 21 references.

References · 9

  1. 2018Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognitioncited by 1,199
  2. 20163D Menagerie: Modeling the 3D shape and pose of animalscited by 310
  3. 2016One-Shot Video Object Segmentationcited by 233
  4. 2018Markerless tracking of user-defined features with deep learningcited by 203
  5. 2019Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"cited by 106
  6. 2018Creatures great and SMAL: Recovering the shape and motion of animals from videocited by 84
  7. 2020Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loopcited by 81
  8. 20203D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single Viewcited by 40
  9. 2020RGBD-Dog: Predicting Canine Pose from RGBD Sensorscited by 35

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 0; 2023: 2; 2024: 4; 2025: 3; 2026: 8.

18 papers.

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  1. 2023GART: Gaussian Articulated Template Modelscited by 121
  2. 2024AniMer: Animal Pose and Shape Estimation Using Family Aware Transformercited by 20
  3. 2024AWOL: Analysis WithOut synthesis using Languagecited by 12
  4. 2024Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Imagescited by 7
  5. 2025AniMer+: Unified Pose and Shape Estimation Across Mammalia and Aves via Family-Aware Transformercited by 7
  6. 2023SPAC-Net: Synthetic Pose-aware Animal ControlNet for Enhanced Pose Estimationcited by 6
  7. 2025DogMo: A Large-Scale Multi-View RGB-D Dataset for 4D Canine Motion Recoverycited by 4
  8. 2026NeuralFur: Animal Fur Reconstruction From Multi-View Imagescited by 4
  9. 2021Equine Pain Behavior Classification via Self-Supervised Disentangled Pose Representationcited by 2
  10. 2025Advances and Trends in the 3D Reconstruction of the Shape and Motion of Animalscited by 2
  11. 20264DEquine: Disentangling Motion and Appearance for 4D Equine Reconstruction from Monocular Videocited by 2
  12. 2026SAM 3D Animal: Promptable Animal 3D Reconstruction from Images in the Wildcited by 2
6 more
  1. 2024CLHOP: Combined Audio-Video Learning for Horse 3D Pose and Shape Estimationcited by 1
  2. 2026Monocular Mesh Recovery and Body Measurement of Female Saanen Goatscited by 1
  3. 2026PRIMA: Boosting Animal Mesh Recovery with Biological Priors and Test-Time Adaptationcited by 1
  4. 2026CORGI: Consistency-Aware 3D Dog Reconstruction from a Single Image in the Wildcited by 0
  5. 2026AnimalLift: Reconstructing Animatable 3D Animals from a Single Image by Learning Canonical Shape, Texture, and Fur Mapscited by 0
  6. 2026ORMA: Optimization-based Monocular 4D Reconstruction of Articulated Animalscited by 0