187 citations · 235 across the 10 of their papers we have counts for
6 papers · 1 filter
Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration
Zhili Li, Kangyang Chai, Zhihao Wang +6
Super-resolution (SR) techniques have made major advances in reconstructing high-resolution images from low-resolution inputs. The increased resolution provides visual enhancement…
TRAJGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations
Maria Despoina Siampou, Gengchen Mai, Ni Lao +4
Multimodal self-supervised learning (MSSL) has emerged as a key paradigm for pretraining geospatial foundation models. However, existing geospatial MSSL methods are mainly designed…
Cross-View Geolocalization and Disaster Mapping with Street-View and VHR Satellite Imagery: A Case Study of Hurricane IAN
Hao Li, Fabian Deuser, Wenping Yina +5
Nature disasters play a key role in shaping human-urban infrastructure interactions. Effective and efficient response to natural disasters is essential for building resilience and…
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…