4 papers
LocDiff: Identifying Locations on Earth by Diffusing in the Hilbert Space
Zhangyu Wang, Zeping Liu, Jielu Zhang +8
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…
TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning
Nemin Wu, Qian Cao, Zhangyu Wang +12
Spatial representation learning (SRL) aims at learning general-purpose neural network representations from various types of spatial data (e.g., points, polylines, polygons, network…
Img2Loc: Revisiting Image Geolocalization using Multi-modality Foundation Models and Image-based Retrieval-Augmented Generation
Zhongliang Zhou, Jielu Zhang, Zihan Guan +5
Geolocating precise locations from images presents a challenging problem in computer vision and information retrieval.Traditional methods typically employ either classification, wh…
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications
Chenjiao Tan, Qian Cao, Yiwei Li +15
The advent of large language models (LLMs) has heightened interest in their potential for multimodal applications that integrate language and vision. This paper explores the capabi…