| license: cc-by-nc-4.0 | |
| pipeline_tag: depth-estimation | |
| # CylinderDepth | |
| **CylinderDepth: Cylindrical Spatial Attention for Multi-View Consistent Self-Supervised Surround Depth Estimation** | |
| [Project Page](https://abualhanud.github.io/CylinderDepthPage/) | [Paper](https://arxiv.org/abs/2511.16428) | [Supplementary Material](https://arxiv.org/src/2511.16428v3/anc/CylinderDepth_supp.pdf) | [Code](https://github.com/abualhanud/CylinderDepth) | |
| CylinderDepth is a geometry-guided method for calibrated, time-synchronized multi-camera rigs that predicts dense metric depth. It addresses depth inconsistency across views by extending the receptive field and applying a cylindrical spatial attention mechanism that aggregates features across images according to their distances on a shared cylinder. | |
| ## Citation | |
| If you find this work useful, please cite our paper: | |
| ```bibtex | |
| @InProceedings{Abualhanud2026, | |
| author = {Abualhanud, Samer and Grannemann, Christian and Mehltretter, Max}, | |
| booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops}, | |
| title = {CylinderDepth: Cylindrical Spatial Attention for Multi-View Consistent Self-Supervised Surround Depth Estimation}, | |
| year = {2026}, | |
| note = {Accepted for publication.} | |
| } | |
| ``` |