mlsanityData to 14 Oct 2026

DogMo: A Large-Scale Multi-View RGB-D Dataset for 4D Canine Motion Recovery

arXiv 2510.24117 ↗First posted 28 Oct 2025cs.CVcited by 4

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Abstract (arXiv)

We present DogMo, a large-scale multi-view RGB-D video dataset capturing diverse canine movements for the task of motion recovery from images. DogMo comprises 1.2k motion sequences collected from 10 unique dogs, offering rich variation in both motion and breed. It addresses key limitations of existing dog motion datasets, including the lack of multi-view and real 3D data, as well as limited scale and diversity. Leveraging DogMo, we establish four motion recovery benchmark settings that support systematic evaluation across monocular and multi-view, RGB and RGB-D inputs. To facilitate accurate motion recovery, we further introduce a three-stage, instance-specific optimization pipeline that fits the SMAL model to the motion sequences. Our method progressively refines body shape and pose through coarse alignment, dense correspondence supervision, and temporal regularization. Our dataset and method provide a principled foundation for advancing research in dog motion recovery and open up new directions at the intersection of computer vision, computer graphics, and animal behavior modeling.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 49 of its 71 references that are in the map. First posted on arXiv 28 Oct 2025.

Builds on

49 of 71 references.

References · 49

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37 more
  1. 2023BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motioncited by 236
  2. 2023WHAM: Reconstructing World-grounded Humans with Accurate 3D Motioncited by 206
  3. 2021BANMo: Building Animatable 3D Neural Models from Many Casual Videoscited by 197
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  17. 2022BARC: Learning to Regress 3D Dog Shape from Images by Exploiting Breed Informationcited by 51
  18. 2023Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shapecited by 44
  19. 20203D Bird Reconstruction: a Dataset, Model, and Shape Recovery from a Single Viewcited by 40
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 4.

4 papers.

  1. 2026SMAL-pets: SMAL Based Avatars of Pets from Single Imagecited by 1
  2. 2026InterPet4D: A Multimodal 4D Human-Pet Interaction Dataset for Pet Motion Generationcited by 1
  3. 2026CORGI: Consistency-Aware 3D Dog Reconstruction from a Single Image in the Wildcited by 0
  4. 2026ORMA: Optimization-based Monocular 4D Reconstruction of Articulated Animalscited by 0