LEAP: Making Privileged Geometry Supervision Effective for Visuomotor Learning
cs.RO
Submitted: 2026-10-04
Updated: 2026-10-04
Sources
- Learning Precise 3D Manipulation from Multiple Uncalibrated Cameras
- Merging and Disentangling Views in Visual Reinforcement Learning for Robotic Manipulation
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- Mind-VLA: Instruction-Aware Spatial Representation Alignment for Vision-Language-Action Models
- Multi-view Disentanglement for Reinforcement Learning with Multiple Cameras
- FOCAL-VLA: Subtask-Guided Geometry Distillation and Implicit World Modeling for Vision-Language-Action Models
- Act3D: 3D Feature Field Transformers for Multi-Task Robotic Manipulation
- RVT: Robotic View Transformer for 3D Object Manipulation
- ELAN4D: Embodiment-Centric 4D Supervision for Vision-Language-Action Models via Plug-and-Play Adaptation
- Vision-Based Manipulators Need to Also See from Their Hands
- Look Closer: Bridging Egocentric and Third-Person Views with Transformers for Robotic Manipulation
- PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning
- Lift3D Foundation Policy: Lifting 2D Large-Scale Pretrained Models for Robust 3D Robotic Manipulation
- 3D Diffuser Actor: Policy Diffusion with 3D Scene Representations
- Pri4R: Learning World Dynamics for Vision-Language-Action Models with Privileged 4D Representation
- PointVLA: Injecting the 3D World into Vision-Language-Action Models
- Spatial Forcing: Implicit Spatial Representation Alignment for Vision-language-action Model
- QDepth-VLA: Quantized Depth Prediction as Auxiliary Supervision for Vision-Language-Action Models
- ReViP: Mitigating False Completion in Vision-Language-Action Models with Vision-Proprioception Rebalance
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