Abstract
Persistent semantic occupancy mapping is essential for embodied scene understanding. However, perspective-based systems provide limited spatial coverage, while existing panoramic methods primarily predict local volumes from single observations. We introduce PanOVOcc, a training-free framework for persistent open-vocabulary semantic occupancy mapping from panoramic sequences. PanOVOcc unifies panoramic SLAM, open-vocabulary perception, and long-term spatial voxel memory within an online architecture, continuously integrating geometric and semantic evidence into a global, language-queryable map. To facilitate systematic evaluation of this setting, we establish Pan-Replica and Pan-Holo360D, two benchmarks pairing continuous panoramic RGB-D sequences with scene-level semantic occupancy ground truth across synthetic and real-world scenes. Compared with the strongest evaluated baseline for each metric, PanOVOcc improves occupancy IoU and semantic mIoU by absolute +20.03 and +7.06 on Pan-Replica, and by +43.26 and +20.16 on Pan-Holo360D, respectively. The source code and the established benchmarks will be available at https://github.com/bakereet/PanOVOcc.
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Cite this article
APA 7
Kuang, D., Duan, M., Wang, Y., Peng, W., & Yang, K. (2026). PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory. https://omanscience.com/en/articles/panovocc-panoramic-embodied-open-vocabulary-occupancy-mapping-with-long-term-spatial-voxel-memory
MLA 9
Kuang, Di, et al. "PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory." https://omanscience.com/en/articles/panovocc-panoramic-embodied-open-vocabulary-occupancy-mapping-with-long-term-spatial-voxel-memory.
Chicago (author–date)
Kuang, Di, Mengfei Duan, Yuhang Wang, Weixing Peng, and Kailun Yang. 2026. "PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory." https://omanscience.com/en/articles/panovocc-panoramic-embodied-open-vocabulary-occupancy-mapping-with-long-term-spatial-voxel-memory.
Harvard
Kuang, D., Duan, M., Wang, Y., Peng, W. and Yang, K. (2026) 'PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory', Available at: https://omanscience.com/en/articles/panovocc-panoramic-embodied-open-vocabulary-occupancy-mapping-with-long-term-spatial-voxel-memory.
Vancouver
Kuang D, Duan M, Wang Y, Peng W, Yang K. PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory. https://omanscience.com/en/articles/panovocc-panoramic-embodied-open-vocabulary-occupancy-mapping-with-long-term-spatial-voxel-memory
IEEE
D. Kuang, M. Duan, Y. Wang, W. Peng, and K. Yang, "PanOVOcc: Panoramic Embodied Open-Vocabulary Occupancy Mapping with Long-term Spatial Voxel Memory," https://omanscience.com/en/articles/panovocc-panoramic-embodied-open-vocabulary-occupancy-mapping-with-long-term-spatial-voxel-memory.