DexCast: Learning Real-World Dexterous Control from Human Videos
cs.RO, cs.AI
Submitted: 2026-10-10
Updated: 2026-10-14
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- CordViP: Correspondence-based Visuomotor Policy for Dexterous Manipulation in Real-World
- DexGraspVLA: A Vision-Language-Action Framework Towards General Dexterous Grasping
- Act3D: 3D Feature Field Transformers for Multi-Task Robotic Manipulation
- Teach a Robot to FISH: Versatile Imitation from One Minute of Demonstrations
- Equivariant Diffusion Policy
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- EgoLive: A Large-Scale Egocentric Dataset from Real-World Human Tasks
- Leveraging Pretrained Latent Representations for Few-Shot Imitation Learning on a Dexterous Robotic Hand
- VQ-ACE: Efficient Policy Search for Dexterous Robotic Manipulation via Action Chunking Embedding
- Cross-Hand Latent Representation for Vision-Language-Action Models
- 3D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations
- 3D Diffuser Actor: Policy Diffusion with 3D Scene Representations
- EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learning
- RoboWheel: A Data Engine from Real-World Human Demonstrations for Cross-Embodiment Robotic Learning
- HO-Cap: A Capture System and Dataset for 3D Reconstruction and Pose Tracking of Hand-Object Interaction
- Embodied Hands: Modeling and Capturing Hands and Bodies Together
- Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation
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