🌳 Introducing WHU-STree, a new multimodal street tree dataset from Wuhan University, now published in ISPRS Journal of Photogrammetry and Remote Sensing.
Why is it interesting?
• Cross-city coverage: data collected in Nanjing and Shenyang, two cities with very different climates and urban layouts, enabling cross-region generalization studies
• Rich annotations: 21,007 individual street tree instances, 50 species, and 2 morphological attributes
• Multimodal data: temporally aligned LiDAR point clouds high-resolution panoramic images
• Multi-task potential: single-tree inventory, cross-domain generalization, multi-task learning, and domain adaptation
An interesting takeaway from the benchmark:
while multimodal fusion outperforms single-modality baselines, it still does not consistently surpass strong 3D-only methods. This highlights that effective multimodal fusion remains an open challenge.
We hope this dataset can support future research in urban greenery inventory and smart city management.
Code & dataset:
github.com/WHU-USI3DV/WHU-ST…
Paper:
doi.org/10.1016/j.isprsjprs.…
#RemoteSensing #ComputerVision #MultimodalLearning #LiDAR #UrbanComputing #SmartCity #Dataset #ISPRS