egenioussBench is a new geospatial visual localisation benchmark with a non-co-visible test split of 42 smartphone images and a validation split, built on 3D mesh and CityGML reference data.
Uavd4l: A large-scale dataset for uav 6-dof localization
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
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cs.CV 3representative citing papers
AerialMetric is a new benchmark dataset and evaluation suite for adapting monocular metric depth estimation models to real-world UAV aerial views.
Introduces UAVDB dataset for UAV detection/segmentation via PIC point-to-box conversion and SAM2 masks, with YOLO baselines showing PIC+SAM2 outperforms prior annotation methods on IoU.
citing papers explorer
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AerialMetric: Benchmarking and Adapting UAV Monocular Metric Depth Estimation in the Real World
AerialMetric is a new benchmark dataset and evaluation suite for adapting monocular metric depth estimation models to real-world UAV aerial views.
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UAVDB: Point-Guided Masks for UAV Detection and Segmentation
Introduces UAVDB dataset for UAV detection/segmentation via PIC point-to-box conversion and SAM2 masks, with YOLO baselines showing PIC+SAM2 outperforms prior annotation methods on IoU.