mlsanityData to 7 Oct 2026

Dessie: Disentanglement for Articulated 3D Horse Shape and Pose Estimation from Images

arXiv 2410.03438 ↗First posted 4 Oct 2024cs.CVcited by 7

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Abstract (arXiv)

In recent years, 3D parametric animal models have been developed to aid in estimating 3D shape and pose from images and video. While progress has been made for humans, it's more challenging for animals due to limited annotated data. To address this, we introduce the first method using synthetic data generation and disentanglement to learn to regress 3D shape and pose. Focusing on horses, we use text-based texture generation and a synthetic data pipeline to create varied shapes, poses, and appearances, learning disentangled spaces. Our method, Dessie, surpasses existing 3D horse reconstruction methods and generalizes to other large animals like zebras, cows, and deer. See the project website at: urlhttps://celiali.github.io/Dessie/.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 64 of its 84 references that are in the map. First posted on arXiv 4 Oct 2024.

Builds on

64 of 84 references.

References · 64

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  5. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  6. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,764
  7. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,482
  8. 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,893
  9. 2015Fast R-CNNcited by 2,930
  10. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,600
  11. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  12. 2016Stacked Hourglass Networks for Human Pose Estimationcited by 913
38 more
  1. 2017End-to-end Recovery of Human Shape and Posecited by 883
  2. 2020Accelerating 3D Deep Learning with PyTorch3Dcited by 781
  3. 2016Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Imagecited by 692
  4. 2019Learning to Reconstruct 3D Human Pose and Shape via Model-fitting in the Loopcited by 625
  5. 2019VIBE: Video Inference for Human Body Pose and Shape Estimationcited by 615
  6. 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 411
  7. 2023Humans in 4D: Reconstructing and Tracking Humans with Transformerscited by 344
  8. 2021PARE: Part Attention Regressor for 3D Human Body Estimationcited by 334
  9. 2021Deep ViT Features as Dense Visual Descriptorscited by 327
  10. 2018Learning 3D Human Dynamics from Videocited by 315
  11. 20163D Menagerie: Modeling the 3D shape and pose of animalscited by 310
  12. 2020HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimationcited by 304
  13. 2023TEXTure: Text-Guided Texturing of 3D Shapescited by 303
  14. 2022CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimationcited by 237
  15. 2018Learning to Estimate 3D Human Pose and Shape from a Single Color Imagecited by 226
  16. 2022Splicing ViT Features for Semantic Appearance Transfercited by 209
  17. 2017Unite the People: Closing the Loop Between 3D and 2D Human Representationscited by 205
  18. 2022Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representationscited by 195
  19. 2020STAR: Sparse Trained Articulated Human Body Regressorcited by 194
  20. 2021Probabilistic Modeling for Human Mesh Recoverycited by 152
  21. 2021GLAMR: Global Occlusion-Aware Human Mesh Recovery with Dynamic Camerascited by 151
  22. 2020Self-supervised Single-view 3D Reconstruction via Semantic Consistencycited by 127
  23. 2022MagicPony: Learning Articulated 3D Animals in the Wildcited by 111
  24. 2019Cross-Domain Adaptation for Animal Pose Estimationcited by 108
  25. 2019Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"cited by 106
  26. 2022Recovering 3D Human Mesh from Monocular Images: A Surveycited by 103
  27. 2024TokenHMR: Advancing Human Mesh Recovery with a Tokenized Pose Representationcited by 93
  28. 2018Creatures great and SMAL: Recovering the shape and motion of animals from videocited by 84
  29. 2020Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loopcited by 81
  30. 2020Articulation-aware Canonical Surface Mappingcited by 80
  31. 2019Unsupervised Part-Based Disentangling of Object Shape and Appearancecited by 67
  32. 2019Learning from Synthetic Animalscited by 65
  33. 2022LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discoverycited by 65
  34. 2020Unsupervised Shape and Pose Disentanglement for 3D Meshescited by 61
  35. 2024Learning the 3D Fauna of the Webcited by 58
  36. 2022BARC: Learning to Regress 3D Dog Shape from Images by Exploiting Breed Informationcited by 51
  37. 2021From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimationcited by 48
  38. 2019Pretraining boosts out-of-domain robustness for pose estimationcited by 47

50 most cited of 64 All 64 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 3.

7 papers.

  1. 2024DualPM: Dual Posed-Canonical Point Maps for 3D Shape and Pose Reconstructioncited by 10
  2. 2025AniMer+: Unified Pose and Shape Estimation Across Mammalia and Aves via Family-Aware Transformercited by 7
  3. 2025Model-based Metric 3D Shape and Motion Reconstruction of Wild Bottlenose Dolphins in Drone-Shot Videoscited by 4
  4. 2025TwoSquared: 4D Generation from 2D Image Pairscited by 3
  5. 20264DEquine: Disentangling Motion and Appearance for 4D Equine Reconstruction from Monocular Videocited by 2
  6. 2026PRIMA: Boosting Animal Mesh Recovery with Biological Priors and Test-Time Adaptationcited by 1
  7. 2026GenMatter: Perceiving Physical Objects with Generative Matter Modelscited by 0