BKinD-3D: Self-Supervised 3D Keypoint Discovery from Multi-View Videos
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Abstract (arXiv)
Quantifying motion in 3D is important for studying the behavior of humans and other animals, but manual pose annotations are expensive and time-consuming to obtain. Self-supervised keypoint discovery is a promising strategy for estimating 3D poses without annotations. However, current keypoint discovery approaches commonly process single 2D views and do not operate in the 3D space. We propose a new method to perform self-supervised keypoint discovery in 3D from multi-view videos of behaving agents, without any keypoint or bounding box supervision in 2D or 3D. Our method, BKinD-3D, uses an encoder-decoder architecture with a 3D volumetric heatmap, trained to reconstruct spatiotemporal differences across multiple views, in addition to joint length constraints on a learned 3D skeleton of the subject. In this way, we discover keypoints without requiring manual supervision in videos of humans and rats, demonstrating the potential of 3D keypoint discovery for studying behavior.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 30 of its 50 references that are in the map. First posted on arXiv 14 Dec 2022.
Builds on
30 of 50 references.
References · 30
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18 more
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Built on by
Citing papers per year: 2023: 4; 2024: 4; 2025: 2.
10 papers.
- 2023Ponymation: Learning Articulated 3D Animal Motions from Unlabeled Online Videoscited by 21
- 20233D-MuPPET: 3D Multi-Pigeon Pose Estimation and Trackingcited by 12
- 2024UPose3D: Uncertainty-Aware 3D Human Pose Estimation with Cross-View and Temporal Cuescited by 6
- 2025DIMO: Diverse 3D Motion Generation for Arbitrary Objectscited by 6
- 2024Pose Prior Learner: Unsupervised Categorical Prior Learning for Pose Estimationcited by 3
- 2023Mask as Supervision: Leveraging Unified Mask Information for Unsupervised 3D Pose Estimationcited by 2
- 2024Learning Keypoints for Multi-Agent Behavior Analysis using Self-Supervisioncited by 2
- 2023Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)cited by 0
- 2024X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimationcited by 0
- 2025Unsupervised Monocular 3D Keypoint Discovery from Multi-View Diffusion Priorscited by 0
- 2025DIMO: Diverse 3D Motion Generation for Arbitrary Objects10 Nov 2025
- 2025Unsupervised Monocular 3D Keypoint Discovery from Multi-View Diffusion Priors16 Jul 2025
- 2024X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation20 Nov 2024
- 2024Pose Prior Learner: Unsupervised Categorical Prior Learning for Pose Estimation4 Oct 2024
- 2024Learning Keypoints for Multi-Agent Behavior Analysis using Self-Supervision14 Sep 2024
- 2024UPose3D: Uncertainty-Aware 3D Human Pose Estimation with Cross-View and Temporal Cues23 Apr 2024
- 2023Ponymation: Learning Articulated 3D Animal Motions from Unlabeled Online Videos21 Dec 2023
- 2023Mask as Supervision: Leveraging Unified Mask Information for Unsupervised 3D Pose Estimation12 Dec 2023
- 2023Tracking Object Positions in Reinforcement Learning: A Metric for Keypoint Detection (extended version)1 Dec 2023
- 20233D-MuPPET: 3D Multi-Pigeon Pose Estimation and Tracking29 Aug 2023