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Lan Mu

2 accepted papers

2025

LocDiff: Identifying Locations on Earth by Diffusing in the Hilbert Space

NeurIPS 2025poster

Image geolocalization is a fundamental yet challenging task, aiming at inferring the geolocation on Earth where an image is taken. State-of-the-art methods employ either grid-based classification or gallery-based image-location retrieval, whose spatial generalizability significantly suffers if the s…

Cited by 0SourceScholar
2024

TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning

NeurIPS 2024poster

Spatial representation learning (SRL) aims at learning general-purpose neural network representations from various types of spatial data (e.g., points, polylines, polygons, networks, images, etc.) in their native formats. Learning good spatial representations is a fundamental problem for various dow…