StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras
cs.RO, cs.CV, cs.LG
Submitted: 2026-10-08
Updated: 2026-10-08
Project page: https://stereoengine.github.io
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
- StereoPolicy: Improving Robotic Manipulation Policies via Stereo Perception
- MolmoAct2: Action Reasoning Models for Real-world Deployment
- DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning
- Real2Render2Real: Scaling Robot Data Without Dynamics Simulation or Robot Hardware
- StereoCrafter: Diffusion-based Generation of Long and High-fidelity Stereoscopic 3D from Monocular Videos
- SpatialDreamer: Self-supervised Stereo Video Synthesis from Monocular Input
- Mono2Stereo: A Benchmark and Empirical Study for Stereo Conversion
- StereoWorld: Geometry-Aware Monocular-to-Stereo Video Generation
- Restereo: Diffusion stereo video generation and restoration
- ExStereo: Lifting 2D Vision-Language-Action Models to 3D with Explicit Stereo Representations
- Stereo Anything: Unifying Zero-shot Stereo Matching with Large-Scale Mixed Data
- Deep3D: Fully Automatic 2D-to-3D Video Conversion with Deep Convolutional Neural Networks
- DissolveStereo: Coarse Depth Injection for Zero-Shot Stereo Video Generation
- ClearDepth: Enhanced Stereo Perception of Transparent Objects for Robotic Manipulation
- ActiveGlasses: Learning Manipulation with Active Vision from Ego-centric Human Demonstration
- DreamGen: Unlocking Generalization in Robot Learning through Video World Models
- DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos
- World Action Models are Zero-shot Policies
- Cosmos World Foundation Model Platform for Physical AI
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