mlsanityData to 7 Oct 2026

DreaMo: Articulated 3D Reconstruction From A Single Casual Video

arXiv 2312.02617 ↗First posted 5 Dec 2023cs.CV cs.GRcited by 12

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Abstract (arXiv)

Articulated 3D reconstruction has valuable applications in various domains, yet it remains costly and demands intensive work from domain experts. Recent advancements in template-free learning methods show promising results with monocular videos. Nevertheless, these approaches necessitate a comprehensive coverage of all viewpoints of the subject in the input video, thus limiting their applicability to casually captured videos from online sources. In this work, we study articulated 3D shape reconstruction from a single and casually captured internet video, where the subject's view coverage is incomplete. We propose DreaMo that jointly performs shape reconstruction while solving the challenging low-coverage regions with view-conditioned diffusion prior and several tailored regularizations. In addition, we introduce a skeleton generation strategy to create human-interpretable skeletons from the learned neural bones and skinning weights. We conduct our study on a self-collected internet video collection characterized by incomplete view coverage. DreaMo shows promising quality in novel-view rendering, detailed articulated shape reconstruction, and skeleton generation. Extensive qualitative and quantitative studies validate the efficacy of each proposed component, and show existing methods are unable to solve correct geometry due to the incomplete view coverage.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 59 of its 70 references that are in the map. First posted on arXiv 5 Dec 2023.

Builds on

59 of 70 references.

References · 59

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  4. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  5. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  6. 2021Zero-Shot Text-to-Image Generationcited by 4,276
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  8. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,600
  9. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  10. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,483
  11. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
  12. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,285
38 more
  1. 2018Demystifying MMD GANscited by 1,268
  2. 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,194
  3. 2021Volume Rendering of Neural Implicit Surfacescited by 990
  4. 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 641
  5. 2019VIBE: Video Inference for Human Body Pose and Shape Estimationcited by 615
  6. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  7. 2022Latent-NeRF for Shape-Guided Generation of 3D Shapes and Texturescited by 506
  8. 2022HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Videocited by 483
  9. 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
  10. 2021Animatable Neural Radiance Fields for Modeling Dynamic Human Bodiescited by 361
  11. 2018Learning Category-Specific Mesh Reconstruction from Image Collectionscited by 317
  12. 20163D Menagerie: Modeling the 3D shape and pose of animalscited by 310
  13. 2023TEXTure: Text-Guided Texturing of 3D Shapescited by 303
  14. 2022NeuMan: Neural Human Radiance Field from a Single Videocited by 244
  15. 2023DreamBooth3D: Subject-Driven Text-to-3D Generationcited by 235
  16. 2021A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Posecited by 233
  17. 2017Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localizationcited by 207
  18. 2023Text-To-4D Dynamic Scene Generationcited by 204
  19. 2021BANMo: Building Animatable 3D Neural Models from Many Casual Videoscited by 195
  20. 2023Robust Dynamic Radiance Fieldscited by 193
  21. 2018Monocular Total Capture: Posing Face, Body, and Hands in the Wildcited by 162
  22. 2021Editable Free-viewpoint Video Using a Layered Neural Representationcited by 148
  23. 2020Self-supervised Single-view 3D Reconstruction via Semantic Consistencycited by 127
  24. 2021LASR: Learning Articulated Shape Reconstruction from a Monocular Videocited by 115
  25. 2022MagicPony: Learning Articulated 3D Animals in the Wildcited by 111
  26. 2019Three-D Safari: Learning to Estimate Zebra Pose, Shape, and Texture from Images "In the Wild"cited by 106
  27. 2021Neural Actor: Neural Free-view Synthesis of Human Actors with Pose Controlcited by 106
  28. 2020Shape and Viewpoint without Keypointscited by 92
  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. 2019360-Degree Textures of People in Clothing from a Single Imagecited by 75
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  33. 2022LASSIE: Learning Articulated Shapes from Sparse Image Ensemble via 3D Part Discoverycited by 65
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50 most cited of 59 All 59 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 6; 2026: 3.

12 papers.

  1. 2025DreamArt: Generating Interactable Articulated Objects from a Single Imagecited by 25
  2. 2024BAGS: Building Animatable Gaussian Splatting from a Monocular Video with Diffusion Priorscited by 14
  3. 2025RigGS: Rigging of 3D Gaussians for Modeling Articulated Objects in Videoscited by 14
  4. 2026PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual Worldcited by 8
  5. 2025PAD3R: Pose-Aware Dynamic 3D Reconstruction from Casual Videoscited by 7
  6. 2025DogMo: A Large-Scale Multi-View RGB-D Dataset for 4D Canine Motion Recoverycited by 4
  7. 2025Pose Splatter: A 3D Gaussian Splatting Model for Quantifying Animal Pose and Appearancecited by 2
  8. 2024OSN: Infinite Representations of Dynamic 3D Scenes from Monocular Videoscited by 0
  9. 2024Hierarchically Structured Neural Bones for Reconstructing Animatable Objects from Casual Videoscited by 0
  10. 2025HEIR: Learning Graph-Based Motion Hierarchiescited by 0
  11. 2026DailyArt: Discovering Articulation from Single Static Images via Latent Dynamicscited by 0
  12. 2026Instruction-based Image Editing: A Survey on Data, Models, Evaluation, and Applicationscited by 0

Similar, not cited

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  1. 2024DreamDance: Animating Human Images by Enriching 3D Geometry Cues from 2D Poses
  2. 2024SINGAPO: Single Image Controlled Generation of Articulated Parts in Objects
  3. 2025FreeArt3D: Training-Free Articulated Object Generation using 3D Diffusion
  4. 2026Articulated Object Reconstruction from Rest-State Observation
  5. 2023AnimatableDreamer: Text-Guided Non-rigid 3D Model Generation and Reconstruction with Canonical Score Distillation
  6. 2026Artic-O: End-to-End Articulated Object Reconstruction via Latent Geometry Learning
  7. 2026Human Video Generation from a Single Image with 3D Pose and View Control
  8. 2023SiTH: Single-view Textured Human Reconstruction with Image-Conditioned Diffusion