Humanoid-OmniOcc: Stereo-Based Full-View Occupancy Dataset for Embodied AI
Occupancy prediction at voxel-level granularity is essential for safe robotic navigation and interaction in complex environments. Existing occupancy datasets, however, are predominantly designed for autonomous driving with vehicle-centric biases -- forward-facing cameras, far-field geometry, and static road priors -- limiting their applicability to embodied humanoid perception. We present Humanoid-OmniOcc, a large-scale panoramic stereo-based occupancy dataset tailored for humanoid robots. The dataset encompasses 15 diverse simulated indoor scenes and 5 real-world environments, yielding over 155K samples with broad scene and style diversity. Importantly, the dataset is designed around a R...
| Authors | Xianda Guo, Bohao Zhang, Chenwei Huang et al. |
|---|---|
| Primary category | cs.RO |
| Published | 22 June 2026 |
| Last updated at source | 22 June 2026 |
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