7 citations · 12 across the 12 of their papers we have counts for
14 papers
Deep learning enables urban change profiling through alignment of historical maps
Sidi Wu, Yizi Chen, Maurizio Gribaudi +4
Prior to modern Earth observation technologies, historical maps provide a unique record of long-term urban transformation and offer a lens on the evolving identity of cities. Howev…
MapSAM2: Adapting SAM2 for Automatic Segmentation of Historical Map Images and Time Series
Xue Xia, Randall Balestriero, Tao Zhang +4
Historical maps are unique and valuable archives that document geographic features across different time periods. However, automated analysis of historical map images remains a sig…
Geospatial Question Answering on Historical Maps Using Spatio-Temporal Knowledge Graphs and Large Language Models
Ziyi Liu, Sidi Wu, Lorenz Hurni
Recent advances have enabled the extraction of vectorized features from digital historical maps. To fully leverage this information, however, the extracted features must be organiz…
Generative AI in Map-Making: A Technical Exploration and Its Implications for Cartographers
Claudio Affolter, Sidi Wu, Yizi Chen +1
Traditional map-making relies heavily on Geographic Information Systems (GIS), requiring domain expertise and being time-consuming, especially for repetitive tasks. Recent advances…
Constructing AI ethics narratives based on real-world data: Human-AI collaboration in data-driven visual storytelling
Mengyi Wei, Chenjing Jiao, Chenyu Zuo +2
AI ethics narratives have the potential to shape the public accurate understanding of AI technologies and promote communication among different stakeholders. However, AI ethics nar…
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps
Xue Xia, Randall Balestriero, Tao Zhang +1
Tracking geographic entities from historical maps, such as buildings, offers valuable insights into cultural heritage, urbanization patterns, environmental changes, and various his…
MapSAM: Adapting Segment Anything Model for Automated Feature Detection in Historical Maps
Xue Xia, Daiwei Zhang, Wenxuan Song +2
Automated feature detection in historical maps can significantly accelerate the reconstruction of the geospatial past. However, this process is often constrained by the time-consum…
An Efficient System for Automatic Map Storytelling -- A Case Study on Historical Maps
Ziyi Liu, Claudio Affolter, Sidi Wu +2
Historical maps provide valuable information and knowledge about the past. However, as they often feature non-standard projections, hand-drawn styles, and artistic elements, it is…
A roadmap for generative mapping: unlocking the power of generative AI for map-making
Sidi Wu, Katharina Henggeler, Yizi Chen +1
Maps are broadly relevant across various fields, serving as valuable tools for presenting spatial phenomena and communicating spatial knowledge. However, map-making is still largel…
Probabilistic road classification in historical maps using synthetic data and deep learning
Dominik J. Mühlematter, Sebastian Schweizer, Chenjing Jiao +3
Historical maps are invaluable for analyzing long-term changes in transportation and spatial development, offering a rich source of data for evolutionary studies. However, digitizi…
StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation
Sidi Wu, Yizi Chen, Samuel Mermet +4
Most image-to-image translation models postulate that a unique correspondence exists between the semantic classes of the source and target domains. However, this assumption does no…
Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical Maps
Sidi Wu, Yizi Chen, Konrad Schindler +1
Historical maps provide useful spatio-temporal information on the Earth's surface before modern earth observation techniques came into being. To extract information from maps, neur…
Inferring Implicit 3D Representations from Human Figures on Pictorial Maps
Raimund Schnürer, A. Cengiz Öztireli, Magnus Heitzler +2
In this work, we present an automated workflow to bring human figures, one of the most frequently appearing entities on pictorial maps, to the third dimension. Our workflow is base…
Cartographic Relief Shading with Neural Networks
Bernhard Jenny, Magnus Heitzler, Dilpreet Singh +3
Shaded relief is an effective method for visualising terrain on topographic maps, especially when the direction of illumination is adapted locally to emphasise individual terrain f…