Track, Articulate, Act: Generating Articulation from Casual Human Videos

arXiv:2609.19119 · cs.CV · Submitted 2026-09-16 · Read on arXiv

cs.CV

Submitted: 2026-09-16

Updated: 2026-09-16

Terminology

• Computer Vision and Pattern Recognition — 10× in this paper
• Alignment — 7× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• CVF International Conference on Computer Vision — 4× in this paper
• Digital Twin — 4× in this paper · explained in 5 episodes
• Point Clouds — 4× in this paper · explained in 2 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Conference on Robot Learning — 3× in this paper
• World Model — 3× in this paper · explained in 7 episodes
• Affordance — 2× in this paper · explained in 1 episode
• 3D Gaussian Splatting — 1× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Angular Error — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 4 episodes
• Core — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Gaussian Splatting — 1× in this paper · explained in 4 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• In European Conference on Computer Vision — 1× in this paper
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Vision-language models — 1× in this paper · explained in 2 episodes

Sources

• sim2art: Accurate Articulated Object Modeling from a Single Video using Synthetic Training Data Only
• Articulation in Prime: Primitive-Based Articulated Object Understanding from a Single Casual Video
• MotionForesight: Re-purposing Video Models for Future 3D Scene-Flow Prediction
• SAM 3: Segment Anything with Concepts
• Large Video Planner Enables Generalizable Robot Control
• Dexterous Manipulation Policies from RGB Human Videos via 3D Hand-Object Trajectory Reconstruction
• World Models for Learning Dexterous Hand-Object Interactions from Human Videos
• Articulat3D: Reconstructing Articulated Digital Twins From Monocular Videos with Geometric and Motion Constraints
• Any4D: Unified Feed-Forward Metric 4D Reconstruction
• Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model
• NovaFlow: Zero-Shot Manipulation via Actionable Flow from Generated Videos
• ART: Articulated Reconstruction Transformer
• Video Generators are Robot Policies
• Depth Anything 3: Recovering the Visual Space from Any Views
• VideoArtGS: Building Digital Twins of Articulated Objects from Monocular Video
• VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
• Real2Code: Reconstruct Articulated Objects via Code Generation
• TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking
• SPIDER: Scalable Physics-Informed Dexterous Retargeting
• Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modeling

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